Workflow Templates

Context Hey! I'm Samir, a Supply Chain Data Scientist from Paris who spent six years in China studying and working while struggling to learn Mandarin. I know the challenges of mastering a complex language like Chinese and my greatest support was flash cards. Therefore, I designed this workflow to support fellow Mandarin learners by automating flashcard creation using n8n, so they can focus more on learning and less on manual data entry. 📬 For business inquiries, you can add me on Here Who is this template for? This workflow template is designed for language learners and educators who want to automate the creation of flashcards for Mandarin (or any other language) using Google Translate API, an AI agent for phonetic transcription and generating an illustrative sentence and a free image retrieval API. Why? If you use the open-source application Anki, this workflow will help you automatically generate personalized study materials. How? Let us imagine you want to learn how to say the word Contract in Mandarin. The workflow will automatically Translate the word in Simplified Mandarin (Mandarin: 合同). Provide the phonetic transcription (Pinyin: Hétóng) Generate an example sentence (Example: 我们签订了一份合同.) Download an illustrative picture (For example, a picture of a contract signature) All these fields are automatically recorded in a Google Sheet, making it easy to import into Anki and generate flashcards instantly What do I need to start? This workflow can be used with the free tier plans of the services used. It does not require any advanced programming skills. Prerequisite A Google Drive Account with a folder including a Google Sheet API Credentials: Google Drive API, Google Sheets API and Google Translate API activated with OAuth2 credentials A free API key of pexels.com A google sheet with the columns Next Follow the sticky notes to set up the parameters inside each node and get ready to pump your learning skills. I have detailed the steps in a short tutorial 👇 🎥 Check My Tutorial Notes This workflow can be used for any language. In the AI Agent prompt, you just need to replace the word pinyin with phonetic transcription. You can adapt the trigger to operate the workflow in the way you want. These operations can be performed by batch or triggered by Telegram, email, or webhook. If you want to learn more about how I used Anki flash cards to learn mandarin: 🈷️ Blog Article about Anki Flash Cards This workflow has been created with N8N 1.82.1 Submitted: March 17th, 2025

This workflow appends, lookup, updates, and reads data from a Google Sheet spreadsheet. Set node: The Set node is used to generate data that we want to add to Google Sheets. Depending on your use-case you might have data coming from a different source. For example, you might be fetching data from a WebHook call. Add the node that will fetch the data that you want to add to the Google Sheet. Use can then use the Set node to set the data that you want to add to the Google Sheets. Google Sheets node: This node will add the data from the Set node in a new row to the Google Sheet. You will have to enter the Spreadsheet ID and the Range to specify which sheet you want to add the data to. Google Sheets1 node: This node looks for a specific value in the Google Sheet and returns all the rows that contain the value. In this example, we are looking for the value Berlin in our Google Sheet. If you want to look for a different value, enter that value in the Lookup Value field, and specify the column in the Lookup Column field. Set1 node: The Set node sets the value of the rent by $100 for the houses in Berlin. We pass this new data to the next nodes in the workflow. Google Sheets2 node: This node will update the rent for the houses in Berlin with the new rent set in the previous node. We are mapping the rows with their ID. Depending on your use-case, you might want to map the values with a different column. To set this enter the column name in the Key field. Google Sheets3 node: This node returns the information from the Google Sheet. You can specify the columns that should get returned in the Range field. Currently, the node fetches the data for columns A to D. To fetch the data only for columns A to C set the range to A:C. This workflow can be broken down into different workflows each with its own use case. For example, we can have a workflow that appends new data to a Google Sheet, and another workflow that lookups for a certain value and returns that value. You can learn to build this workflow on the documentation page of the Google Sheets node.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically analyzes purchase trends and consumer behavior patterns to identify market opportunities and optimize business strategies. It saves you time by eliminating the need to manually analyze sales data and provides insights into buying patterns, seasonal trends, and customer preferences. Overview This workflow automatically scrapes e-commerce platforms, marketplace data, and sales analytics to extract purchase trends, product popularity, and consumer behavior insights. It uses Bright Data to access sales data and AI to intelligently analyze purchasing patterns, seasonal trends, and market opportunities. Tools Used n8n**: The automation platform that orchestrates the workflow Bright Data**: For scraping e-commerce and marketplace platforms without being blocked OpenAI**: AI agent for intelligent purchase trend analysis and forecasting Google Sheets**: For storing purchase trend data and analysis results 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 MCP Client node Set Up OpenAI: Configure your OpenAI API credentials Configure Google Sheets: Connect your Google Sheets account and set up your trend analysis spreadsheet Customize: Define target marketplaces and trend analysis parameters Use Cases E-commerce Strategy**: Identify trending products and market opportunities Product Development**: Understand consumer preferences and demand patterns Marketing Planning**: Optimize campaigns based on seasonal purchase trends Business Intelligence**: Make data-driven decisions using market trend insights 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 #purchasetrends #marketanalysis #brightdata #webscraping #ecommerce #n8nworkflow #workflow #nocode #trendanalysis #consumerinsights #marketresearch #salesanalytics #businessintelligence #markettrends #customerinsights #ecommerceanalysis #salesdata #marketforecasting #consumerdata #purchaseanalysis #retailanalytics #marketinsights #demandforecasting #salestrends #consumertrends #marketintelligence #buyingpatterns #marketdemand

This automated n8n workflow qualifies B2B leads via voice calls using the VAPI API and integrates the collected data into Google Sheets. It triggers when a new lead’s phone number is added, streamlining lead qualification and data capture. What is VAPI? VAPI is an API service that enables voice call automation, used here to qualify leads by capturing structured data through interactive calls. Good to Know VAPI API calls may incur costs based on usage; check VAPI pricing for details. Ensure Google Sheets access is properly authorized to avoid data issues. Use credential fields for the HTTP Request node 'Bearer token' instead of hardcoding. Use a placeholder Google Sheet document ID (e.g., "your-sheet-id-placeholder") to avoid leaking private data. How It Works Detect when a new phone number is added for a lead using the New Lead Captured node. Use the Receive Lead Details from VAPI node to capture structured data (name, company, challenges) via a POST request. Trigger an outbound VAPI call to qualify the lead with the Initiate Voice Call (VAPI) node. Store the collected data into a Google Sheet using the Save Qualified Lead to CRM Sheet node. Send a success response back to VAPI with the Send Call Data Acknowledgement node. How to Use Import the workflow into n8n. Configure VAPI API credentials in the HTTP Request node using credential fields. Set up Google Sheets API access and authorize the app. Create a Google Sheet with the following columns: Name (text), Company (text), Challenges (text), Date (date). Test with a sample lead phone number to verify call initiation and data storage. Adjust the workflow as needed and retest. Requirements VAPI API credentials Google Sheets API access Customizing This Workflow Modify the Receive Lead Details from VAPI node to capture additional lead fields or adjust call scripts for specific industries.

This workflow provides automated access to the Black Forest Labs Flux Krea Dev AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for image generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete image generation process using the Black Forest Labs Flux Krea Dev model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: An opinionated text-to-image model from Black Forest Labs in collaboration with Krea that excels in photorealism. Creates images that avoid the oversaturated "AI look". Key Capabilities High-quality image generation from text prompts** Advanced AI-powered visual content creation** Customizable image parameters and styles** Text-to-image transformation capabilities** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Black Forest Labs/flux-krea-dev AI model Black Forest Labs Flux Krea Dev**: The core AI model for image generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Image Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Creation**: Generate unique images for blogs, social media, and marketing materials Design Prototyping**: Create visual concepts and mockups for design projects Art & Creativity**: Produce artistic images for personal or commercial use Marketing Materials**: Generate eye-catching visuals for campaigns and advertisements Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #imagegeneration #aiart #texttoimage #visualcontent #aiimages #generativeart #flux #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

Who's it for This workflow is ideal for AI developers running multi-agent systems in n8n who need to quantitatively evaluate tool usage behavior. If you're building autonomous agents and want to verify their decisions against ground-truth expectations, this workflow gives you plug-and-play observability. What it does This template uses n8n's built-in Evaluation Trigger and Evaluation nodes to assess whether an AI agent correctly used all the expected tools. It supports: Dataset-driven testing of agent behavior Logging actual tools to compare them with the expected tools Assigning performance metrics (tool_called = true/false) Persisting output back to Google Sheets for further debugging The workflow can be triggered by either the chat input or the dataset row evaluation. It routes through a multi-tool agent node powered by the best LLMs. The agent has access to tools such as web search, calculator, vector search, and summarizer tools. The workflow then aims to validate tool use decisions by extracting the intermediate steps from the agent (i.e., action + observation) and comparing the tools that were called with the expected tools. If the tools that were called during the workflow execution match, then it's a pass; otherwise, it's documented as a fail. The evaluation nodes take care of that process.  How to set it up Connect your Google Sheets OAuth2 credential. Replace the document with your own test dataset. Set your desired models and configure the different agent tools, such as the summarizer and vector store. The default vector store used is Qdrant, so the user must create this vector store with a few samples of queries + web search results. Run from either the chat trigger or the evaluation trigger to test. Requirements Google Sheets OAuth2 credential OpenRouter / OpenAI credentials for AI agents and embeddings Firecrawl and Qdrant credentials for web + vector search How to customize Edit the Search Agent system message to define tool selection behavior Add more metric columns in the Evaluation node for complex scoring Add new tool nodes and link them to the agent block Swap in your own summarizer

🔥 Automated Daily Firecrawl Scraper with Telegram Alerts Get structured insights scraped daily from the web using Firecrawl’s AI extraction engine — then send them directly to your Telegram chat. 🧰 What this workflow does: This workflow automatically scrapes specific structured data from any webpage every day at a scheduled time using the Firecrawl API, checks if results are returned, and then sends the formatted results to Telegram. For step-by-step video tutorials of n8n builds, check out my channel: https://www.youtube.com/@Automatewithmarc 🧭 How It Works: 🕐 Schedule Trigger (Daily at 6PM) Starts the workflow every day at a set time. 🌐 Firecrawl POST Request Sends a custom extraction prompt and schema to Firecrawl, targeting any list of URLs you provide. ⏳ 30 Seconds Wait Waits to give Firecrawl enough time to complete processing. 📥 GET Firecrawl Result Fetches the extraction results using the request ID. 🔁 Loop with IF Node Checks whether data is returned. If not, waits another 15 seconds and retries. 🧹 Format & Clean (Set Node) Prepares and formats the extracted result into a readable message. 📲 Telegram Message Node Delivers the structured data directly to your Telegram channel or group. 🔧 Requirements: ✅ Firecrawl API Key (Header Auth) ✅ Telegram Bot Token & Chat ID 💡 Use Cases: Extract structured data (like product info or events) from niche websites Automate compliance monitoring or intelligence gathering Create market alert bots with real-time info delivery 🛠 Customization Ideas: Swap Telegram with Gmail, Discord, or Slack Expand schema to include more complex nested fields Add a Google Sheet node to log daily scraped data Integrate with a summarizer or language model for intelligent summaries Ready to automate your web intelligence gathering? 🧠 Let Firecrawl do the scraping — and let this workflow do the rest.

How to use Get a .csv file with your contacts (you can download this from any contact manager app) Set API key for Google Drive API, and Notion (you need to create a "connection" in Notion) Create Database for your contacts in Notion Choose which properties to extract from the .csv and pass it in to the Notion database. Right now, it transfer 4 pieces of information: full name, email, phone, and company.

This workflow demonstrates the use of static data in n8n. The workflow is built on the concept of polling. Cron node: The Cron node triggers the workflow every minute. You can configure the time based on your use-case. HTTP Request node: This node makes an HTTP Request to an API that returns the position of the ISS. Set node: In the Set node we set the information that we need in the workflow. Since we only need the timestamp, latitude, and longitude we set this in the node. If you need other information, you can set them in this node. Function node: The Function node, checks if the incoming data is similar to the data that was returned in the previous execution or not. If the data is different the Function node returns this new node, otherwise, it returns a message 'No New Items'. The data is also stored as static data with the workflow. Based on your use-case, you can build the workflow further. For example, you can use it send updates to Mattermost or Slack

Automated Invoice Archiving Automatically fetch, store, and extract key information from invoices received via email from your ISP or utility provider (electricity, gas, telecom, water, etc.).The workflow saves the invoices to Google Drive (or optionally to your personal FTP/SFTP server) and logs all invoice details into Google Sheets via AI-powered extraction. Read: Full setup Guide How it works Scheduled TriggerRuns the workflow at a selected interval (e.g., every hour). You can freely adjust the timing. Gmail – Fetch MessagesReads your Gmail inbox and retrieves only messages coming from your ISP/utility provider’s email address, filtering for messages with PDF attachments. Gmail – Download Invoice Fetches the full email content and downloads the attached invoice (PDF). Google Drive – Upload File Uploads the invoice into a specific Google Drive folder of your choice. (Optional) Upload to FTP/SFTP Sends a copy of the invoice to your personal server via secure FTP/SFTP. AI Extraction Pipeline Extract PDF Text – converts the PDF into text (OCR not required if text-based). AI Agent (OpenRouter) – understands the invoice content and extracts structured fields (invoice number, date, provider name, total amount, tax info, line items, etc.) Code Node – sanitizes and parses the JSON from the AI model. Google Sheets – Append Invoice DataAdds a new row to your Google Sheet with all parsed invoice fields. (Optional) CleanupAutomatically deletes:– the Gmail message– the temporary file in Google Drive(Useful when you only want your FTP or Sheets copy.) Parameters to configure | Parameter | Description | Recommended configuration | | --- | --- | --- | | Gmail Credentials | OAuth2 credentials needed to read and delete emails. | Create OAuth credentials on Google Cloud → enable Gmail API → paste Client ID & Secret into n8n → “Connect OAuth2”. | | Sender Email Filter | Email address your provider uses to send invoices. | Example: billing@your-isp.com, invoices@utility.it, ciao@octopusenergy.it | | Google Drive Folder | Destination folder for saving invoices. | Copy the folder ID from the Drive URL and paste it into folderId. | | Google Drive Credentials | OAuth2 connection for file uploads/deletions. | Same Google Cloud project → enable Drive API → OAuth connect in n8n. | | FTP/SFTP Server (optional) | Upload invoices to your private server. | Host / IP · Port · Username · Password or SSH Key · Destination path (e.g. /home/user/invoices/). | | AI Model (OpenRouter) | Large-language model used to parse invoice text. | Example: gpt-4.1, llama-3.1, or any preferred OpenRouter model. | | Google Sheets Document | Destination spreadsheet for structured data. | Create a Sheet → add columns (Vendor, Invoice Number, Date, Amount, Service Type, etc.) → insert documentId & sheet name. | | Sheets Credentials (Service Account) | Used for writing into Google Sheets. | Create Service Account → download JSON → add to n8n → share the Sheet with the Service Account email. | | Trigger Interval | How often the workflow checks for new invoices. | Every hour · every 30 minutes · daily at set ti | Node-by-node breakdown 1. Schedule Trigger Runs at the interval you choose (default: hourly).Start → triggers entire workflow. 2. Gmail – Get Many Messages Filters inbox items using: Sender email** (your ISP/utility address) Has attachment** Unread or recent messages** Downloads metadata + attachment references. 3. Filter – Contains Attachment Ensures only messages with binary attachments continue. 4. Gmail – Get Invoice Downloads: Full email JSON The invoice PDF (binary data) 5. Google Drive – Upload File Uploads invoice PDF with a dynamic filename: {{ $json.from.value[0].name }}-{{ $json.date }}.pdf Requires: Google Drive OAuth2 credentials Folder ID (destination directory) 6. HTTP Request – Download File Retrieves the raw PDF file from Google Drive for further processing. 7. (Optional) FTP/SFTP Upload Uploads the PDF to your server using: Host / IP Port (default 22) Username Password or private key Destination path Filename is sanitized to ensure Unix compatibility. 8. (Optional) Delete Temporary File Deletes the Google Drive file if you don’t want duplicates. 9. (Optional) Delete Gmail Message Removes the original email once processed (optional inbox cleanup). 10. Extract from File (PDF → Text) Reads the PDF and extracts raw text for AI processing. 11. OpenRouter Chat Model LLM backend for the AI agent. Provides: invoice parsing field extraction structured reasoning 12. AI Agent – Extract Invoice Fields The agent is instructed to return strict JSON only, containing keys such as: vendor_name invoice_number invoice_date total_amount tax_details line_items[] po_number po_date Works for most standard PDF invoices. 13. Code – Clean & Parse JSON Sanitizes the AI output: Removes markdown fences Extracts valid JSON Parses into a clean JS object If the AI output is malformed, debugging info is returned. 14. Google Sheets – Append Data Appends the extracted fields into a structured row.Example mappings: Vendor** → {{ $json.vendor_name }} Invoice Number** → {{ $json.invoice_number }} Date** → {{ $json.invoice_date }} Amount** → {{ $json.total_amount }} Service Type** → {{ $json.line_items[0].description }} 💡 Tips & best practices Add multiple sender filters if you have more than one utility provider. Ensure invoices are text-based PDFs for best extraction results. Use Google Drive as a reliable long-term archive, or keep only FTP if you prefer local storage. Create charts in Google Sheets for tracking: Monthly utility cost trends Year-over-year comparison Consumption spikes (if included in invoices) ⚠️ Important notes Utility invoices contain personal and financial data. Keep your FTP/SFTP server secure. Google APIs require proper OAuth2 or Service Account setup; misconfiguration may cause permission errors. This workflow is for personal automation, not a replacement for official fiscal archiving. AI extraction quality depends on invoice formatting and the model you choose.

This workflow demonstrates how CSV file can be automatically imported into existing MySQL database. Before running the workflow please make sure you have a file on the server: /home/node/.n8n/concerts-2023.csv And the content of the file is the following: Date,Band,ConcertName,Country,City,Location,LocationAddress, 2023-05-28,Ozzy Osbourne,No More Tours 2 - Special Guest: Judas Priest,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-05-08,Elton John,Farewell Yellow Brick Road Tour 2023,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-05-26,Hans Zimmer Live,Europe Tour 2023,Germany,Berlin,Mercedes-Benz Arena Berlin,"Mercedes-Platz 1, 10243 Berlin-Friedrichshain", 2023-07-07,Depeche Mode,Memento Mori World Tour 2023,Germany,Berlin,Olympiastadion Berlin,"Olympischer Platz 3, 14053 Berlin-Charlottenburg", The detailed process is explained in the tutorial https://blog.n8n.io/import-csv-into-mysql

This workflow demonstrates how easy it is to export SQL query to CSV automatically! Before running the workflow please make sure you have access to a local or remote MSSQL server with a sample AdventureWorks database. The detailed process is explained in the tutorial https://blog.n8n.io/sql-export-to-csv/