Workflow Templates

Who we are We are Aprende n8n, the first n8n Spanish course for all n8n lovers. If you want to learn more, you can find out more at Aprende n8n. Task goal This task allows extracting data from any email body with a NoCode snippet. An small explanation You receive an email when a user submits a form from your website. All those emails usually have the same structure as the next one: Name: Miquel Email: miquel@aprenden8n.com Subject: Welcome aboard Message: Hi Miquel! Thank you for your signup! This task allows to parse any email body and assign all values to the defined labels, getting an output like this: { "Name": "Miquel", "Email": "miquel@aprenden8n.com", "Subject": "Welcome aboard", "Message" "Hi Miquel! Thank you for your signup!" } After importing it When you import the import, you get the next task in your n8n: We recommend importing this workflow into your current task and adapting it. You define a couple of variables in the "Set values" SET: body: the email body you want to parse. You can add this as an expression from previous variables. labels: the keywords you want to detect and parse. Labels are case insensitive. We define the next values: Body Name: Miquel Email: miquel@aprenden8n.com Subject: Welcome aboard Message: Hi Miquel! Thank you for your signup! Labels Name,Email,Subject,Message A screenshot of the Set output is the next one If we check the "Function item" Node, we get the next content after executing the task: Capabilities The task has the next features: You can detect as many labels as you want. Label detection is case insensitive. You can use the snippet as an independent workflow to call it generically, adding the Function item to the workflow and passing body and labels as paremeters. Limitations This task has limitations: The parser only accepts the multiline values at the end of the email. Help and comments If you have any doubt about this snippet, please, contact us at miquel@aprenden8n.com. You can contact us at Aprende n8n or in the Spanish n8n community

This workflow shows how to sum multiple items of data, like you would in Excel or Airtable when summing up the total of a column. It uses a Function node with some javascript to perform the aggregation of numeric data. The first node is simply mock data to avoid needing a credential to run the workflow. The second node actually performs the summation - the javascript has various comments in case you need to edit the JS. For example, to sum multiple items of data. Below is an example of the type of data this workflow can sum - so anything that is in a tabular form (Airtable, GSHeets, Postgres etc).

This workflow extends n8n and uses R language graphic capabilities. This is a Telegram bot which fetches weather data via the openweathermap.org API, plots an image using ggoplot2 package from R and sends the image to the Telegram user.

v1 Helper ℹ️ This workflow is to be run after upgrading to n8n v1. This workflow returns all locations where a node in an active workflow contains a parameter using an expression extension affected by v1 changes. For every location, please check that the workflow still behaves as intended.

The workflow starts by listening for messages from Telegram users. The message is then processed, and based on its content, different actions are taken. If it's a regular chat message, the workflow generates a response using the OpenAI API and sends it back to the user. If it's a command to create an image, the workflow generates an image using the OpenAI API and sends the image to the user. If the command is unsupported, an error message is sent. Throughout the workflow, there are additional nodes for displaying notes and simulating typing actions.

This workflow allows you to create, add an attachment, and send a draft using the Microsoft Outlook node. Microsoft Outlook node: This node creates a draft message with HTML content. You can either set the content as Text or HTML. You can also add the recipients to the draft in this node. HTTP Request node: This node fetches the logo of n8n from a URL and returns the binary data. You might want to fetch files from your machine or another email or a database. You can replace this node with the relevant node. Microsoft Outlook1 node: This node adds the attachment that we receive from the previous node to the draft message that we created. Microsoft Outlook2 node: This node sends the draft message to a recipient. Since we didn't mention the recipient in the Microsoft Outlook node, we add the recipient in this node. You can also enter multiple recipients.

This n8n workflow is designed to analyze email headers received via a webhook. The workflow splits into two main paths based on the presence of the received and authentication results headers. In the first path, if received headers are present, the workflow extracts IP addresses from these headers and then queries the IP Quality Score API to gather information about the IP addresses, including fraud score, abuse history, organization, and more. Geolocation data is also obtained from the IP-API API. The workflow collects and aggregates this information for each IP address. In the second path, if authentication-results headers are present, the workflow extracts SPF, DKIM, and DMARC authentication results. It then evaluates these results and sets fields accordingly (e.g., SPF pass/fail/neutral). The paths merge their results, and the workflow responds to the original webhook with the aggregated analysis, including IP information and authentication results. Potential issues during setup include ensuring proper configuration of the webhook calls with header authentication, handling authentication and API keys for the IP Quality Score API, and addressing any discrepancies or errors in the logic nodes, such as handling SPF, DKIM, and DMARC results correctly. Additionally, thorough testing with various email header formats is essential to ensure accurate analysis and response.

🧾 Automated Invoice Processing - n8n Workflow 📖 Workflow Description This n8n workflow automates the complete processing of PDF invoices with AI-powered data extraction. The workflow monitors a Google Drive folder, extracts important invoice data, and automatically organizes files in a structured filing system. 🎯 Features 🔍 Automatic monitoring** of a Google Drive folder for new PDF files 🤖 AI-powered data extraction** from invoices (customer, amount, date, etc.) 📁 Intelligent file sorting** by year and month 📝 Automatic renaming** following a consistent schema 📊 Central documentation** in Google Sheets 🔧 Required Integrations Required Accounts: Google Drive (with folder permissions) Google Sheets (with write permissions) Google Gemini API (for AI data extraction) Used n8n Nodes: Google Drive Trigger Google Drive (File Operations) Google Sheets Extract from File (PDF) Information Extractor (LangChain) Google Gemini Chat Model Split in Batches 📋 Workflow Steps in Detail 1. Monitoring & Triggering Google Drive Trigger** monitors a defined input folder Automatically starts when new PDF files are detected Split in Batches** enables batch processing of multiple files 2. File Processing GetFile** downloads PDF files from Google Drive ExtractFromPDF** converts PDF content to text Supports scanned documents as well 3. AI Data Extraction The Information Extractor node with Google Gemini extracts: Company name/sender Customer name and customer number Invoice number and date Net and gross amount Value-added tax Article description Month and year (for sorting) 4. Automatic Filing GetYearFolder** searches/creates year folders GetMonthFolder** searches/creates month folders MoveFile** moves invoice to correct folder UpdateFileName** renames file (schema: "Customer Month Year") 5. Documentation AddToOverview** enters all data into Google Sheets table Enables central overview and analysis ⚙️ Setup Instructions Step 1: Prepare Google Drive Create the following folder structure in Google Drive: 📁 [Input Folder] (e.g., "Invoices-Inbox") 📁 [Main Folder] (e.g., "Accounting") └── 📁 2024 ├── 📁 January ├── 📁 February ├── 📁 March └── ... (all months) └── 📁 2025 └── ... (all months) Step 2: Create Google Sheets Table Create a spreadsheet with the following columns: Customer Number Customer [Company Name] Location Invoice Date Invoice Number VAT Net Amount Month Year Step 3: Configure Workflow Configure Google Drive Trigger: Select your input folder as "Folder to Watch" Set "Event" to "fileCreated" Activate the trigger Search files and folders: Select the same input folder as filter Customize Information Extractor: Adapt attribute names to your needs Change company name in description Adjust system prompt if needed GetYearFolder & GetMonthFolder: Set the correct folder ID for your main folder Check query string for year/month search AddToOverview: Select your Google Sheets table Map columns according to your table 🔧 Customization Options Extend Data Extraction: Add more attributes in the Information Extractor node: { "name": "Payment Terms", "description": "Days until payment due", "required": false } Customize File Naming: Change the schema in the UpdateFileName node: "{{ $('Information Extractor').item.json.output.InvoiceNumber }} - {{ $('Information Extractor').item.json.output.Customer }}" Change Monitoring Interval: In Google Drive Trigger under "Poll Times" select different intervals. 🚨 Important Notes ⚠️ Permissions: Google Drive: Full access to configured folders Google Sheets: Write permission for target table Google Gemini: Valid API key required 📝 Data Format: Works with German number formats (comma as decimal separator) Date format: YYYY-MM-DD Supports various PDF formats 🔄 Error Handling: Workflow fails if folders are missing Incomplete PDFs may lead to incomplete extractions Check logs for troubleshooting 📊 Performance & Limitations Processing time:** 30-60 seconds per invoice Supported formats:** PDF (text and OCR) Batch processing:** Yes, multiple files simultaneously AI accuracy:** ~95% for standardized invoices 🧪 Testing Run Test: Upload a test PDF to the input folder Monitor workflow execution in n8n Check results in Google Sheets Verify correct file movement and renaming Error Diagnosis: For errors: check n8n logs Consider Google API quotas Validate folder permissions 📄 License & Support This workflow can be used and customized freely. For configuration questions or issues, check the n8n community or Google API documentation. Tip: Start with a few test invoices before using the workflow in production!

⚡ UPDATE on May 2025 – added section with all n8n instance webhooks Using n8n a lot? Soar above the limitations of the default n8n dashboard! This template gives you an overview of your workflows, nodes, and tags – all in one place. 💪 Built using XML stylesheets and the Bootstrap 5 library, this workflow is self-contained and does not depend on any third-party software. 🙌 It generates a comprehensive overview JSON that can be easily integrated with other BI tools for further analysis and visualization. 📊 Reach out to Eduard if you need help adapting this workflow to your specific use-case! 🚀 Benefits: Workflow Summary** 📈: Instant overview of your workflows, active counts, and triggers. Left-Side Panel** 📋: Quick access to all your workflows, nodes, and tags for seamless navigation. Workflow Details** 🔬: Deep dive into each workflow's nodes, timestamps, and tags. Node Analysis** 🧩: Identify the most frequently used nodes across your workflows. Tag Organization** 🗂️: Workflows are grouped according to their tags. Webhooks** ⚡: List of all webhook endpoints with the links to workflows. Visually Stunning** 🎨: Clean, intuitive, and easy-to-navigate dashboard design. XML & Bootstrap 5** 🛠️: Built using XML stylesheets and Bootstrap 5, ensuring a self-contained and responsive dashboard. No Dependencies** 🔒: The workflow does not rely on any third-party software. Bootstrap 5 files are loaded via CDN but can be delivered directly from your server. ⚠️ Important note for cloud users Since the cloud version doesn't support environmental variables, please make the following changes: get-nodes-via-jmespath node. Update the instance_url variable: enter your n8n URL instead of {{$env["N8N_PROTOCOL"]}}://{{$env["N8N_HOST"]}} Create HTML node. Please provide the n8n instance URL instead of {{ $env.WEBHOOK_URL }} 🌟Example: Follow me on LinkedIn for more tips on AI automation and n8n workflows!

This workflow automatically manages Acrobat Sign signatures, respond with "intent" to Acrobat-Sign webhooks. Prerequisites Adobe Acrobat Sign and Sign webhook Basic knowledge of JavaScript Nodes Webhook nodes trigger the workflow on new sign intents on a document Respond to Webhook node sets the response headers. Function node processes data returned by the previous node. Set node sets the required values.

Lead Enrichment & Email Discovery from Google Sheets What this workflow does This template automates the enrichment of business leads from a Google Sheet by: Triggering when a row is activated Searching for company information with Serper.dev Generating and validating potential contact pages Scraping company pages with ScrapingBee Extracting emails and updating the sheet Marking rows as finished Prerequisites Google Sheet with columns: business type, city, state, activate Copy the ready-to-use template:** Sheet Template Google Sheets API credentials (from Google Cloud) Serper.dev API key (free tier available) ScrapingBee API key (free tier available) Inputs Google Sheet row:** Must include business type, city, state, activate Set Information Node:** country, country_code, language, result_count (can also be provided via columns in the sheet) Outputs Google Sheet update:** Company names, URLs, found email addresses (comma-separated if multiple), and status updates (Running, Missing information, Finished) Configuration Required Connect Google Sheets node with your Google Cloud credentials Add your Serper.dev API key to the HTTP Request node Add your ScrapingBee API key to the scraping node Adjust search and filtering options as needed How to customize the workflow Send country, country_code, and result_count from the sheet:** Add these as columns in your sheet and update the workflow to read their values dynamically, making your search fully configurable per row. Add more blacklist terms:** Update the code node with additional company names or keywords you want to exclude from the search results. Extract more contact details:** Modify the email extraction code to find other contact info (like phone numbers or social profiles) if needed.

Automated YouTube Shorts Creator with yt-dlp & FFmpeg Description How It Works • Downloads videos/music from YouTube using yt-dlp • Merges assets with dynamic text overlays • Automatically uploads to YouTube as Shorts (9:16 format) • Tracks everything in Google Sheets Set Up Steps (~10 minutes) Install yt-dlp and FFmpeg in your n8n environment Connect Google Sheets (for video/music pools) Set up YouTube OAuth credentials Configure text overlay font (NotoSerif included) Key Features Dual Pipeline System Video Downloader (MP4) + Music Downloader (MP3 with thumbnails) Random pairing for endless combinations Professional Text Overlays Dynamic line wrapping for perfect 9:16 formatting Customizable fonts/colors YouTube API Integration Automatic upload with metadata (titles/descriptions) Privacy/license controls Google Sheets Tracking Logs download paths, YouTube URLs, timestamps Prevents duplicate processing