Workflow Templates

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automates the process of scraping product data from e-commerce websites and using it to fine-tune a custom OpenAI GPT model for generating high-quality marketing copy and product descriptions. Main Use Cases Fine-tune OpenAI models with real product data from hundreds of supported e-commerce websites for marketing content generation. Create custom AI models specialized in writing compelling product descriptions across different industries and platforms. Automate the entire pipeline from data collection to model training using Bright Data's extensive scraper library. Generate marketing copy using your custom-trained model via an interactive chat interface. How it works The workflow operates in two main phases: model training and model usage, organized into these stages: Data Collection & Processing Manually triggered to start the fine-tuning process. Uses Bright Data's web scraper to extract product information from any supported e-commerce platform (Amazon, eBay, Shopify stores, Walmart, Target, and hundreds of other websites). Collects product titles, brands, features, descriptions, ratings, and availability status from your chosen platform. Easily customizable to scrape from different websites by simply changing the dataset configuration and product URLs. Training Data Preparation A Code node processes the scraped product data to create training examples in OpenAI's required JSONL format. For each product, generates a complete training example with: System message defining the AI's role as a marketing assistant. User prompt containing specific product details (title, brand, features, original description snippet). Assistant response providing an ideal marketing description template. Compiles all training examples into a single JSONL file ready for OpenAI fine-tuning. Model Fine-Tuning Uploads the training file to OpenAI using the OpenAI File Upload node. Initiates a fine-tuning job via HTTP Request to OpenAI's fine-tuning API using the GPT-4o-mini model as the base. The fine-tuning process runs on OpenAI's servers to create your custom model. Interactive Chat Interface Provides a chat trigger that allows real-time interaction with your fine-tuned model. An AI Agent node connects to your custom-trained OpenAI model. Users can chat with the model to generate product descriptions, marketing copy, or other content based on the training. Custom Model Integration The OpenAI Chat Model node is configured to use your specific fine-tuned model ID. Delivers responses trained on your product data for consistent, high-quality marketing content. Summary Flow: Manual Trigger → Scrape E-commerce Products (Bright Data) → Process & Format Training Data (Code) → Upload Training File (OpenAI) → Start Fine-Tuning Job (HTTP Request) | Parallel: Chat Trigger → AI Agent → Custom Fine-Tuned Model Response Benefits: Fully automated pipeline from raw product data to trained AI model. Works with hundreds of different e-commerce websites through Bright Data's extensive scraper library. Creates specialized models trained on real e-commerce data for authentic marketing copy across various industries. Scalable solution that can be adapted to different product categories, niches, or websites. Interactive chat interface for immediate access to your custom-trained model. Cost-effective fine-tuning using OpenAI's most efficient model (GPT-4o-mini). Easily customizable with different websites, product URLs, training prompts, and model configurations. Setup Requirements: Bright Data API credentials for web scraping (supports hundreds of e-commerce websites). OpenAI API key with fine-tuning access. Replace placeholder credential IDs and model IDs with your actual values. Customize the product URLs list and Bright Data dataset for your specific website and use case. The workflow can be adapted for any e-commerce platform supported by Bright Data's scraping infrastructure.

Google Sheets to MailChimp Auto-Importer Overview This n8n workflow automatically imports contacts from Google Sheets into your MailChimp mailing list. Perfect for businesses collecting leads through Google Forms, event registrations, or maintaining contact lists in spreadsheets. Key Features 📊 Bulk Import: Process entire Google Sheets at once 🔄 Smart Name Parsing: Automatically splits full names into first and last names 📱 Phone Number Support: Includes phone numbers as merge fields ⚡ Error Resilience: Continues processing even if individual contacts fail 📝 Import Summary: Generates a summary of processed contacts Prerequisites Before using this workflow, ensure you have: An active n8n instance (self-hosted or cloud) A Google account with access to Google Sheets A MailChimp account with at least one audience/list created Basic understanding of n8n workflows Initial Setup Step 1: Import the Workflow Copy the workflow JSON In n8n, click "Import from File" or paste the JSON Save the workflow with a meaningful name Step 2: Configure Google Sheets Connection Click on the "Get Google Sheet Data" node Click on "Credential to connect with" Select "Create New" and choose "Google Sheets OAuth2" Follow the OAuth flow to authenticate your Google account Save the credentials Step 3: Configure MailChimp Connection Click on the "Add to MailChimp" node Click on "Credential to connect with" Select "Create New" and choose "MailChimp OAuth2" or "MailChimp API" For API method: Log into MailChimp Go to Account → Extras → API keys Generate a new API key Copy and paste it into n8n Save the credentials Step 4: Configure Your Specific Settings Google Sheets Settings: Open the "Get Google Sheet Data" node Replace YOUR_GOOGLE_SHEET_ID with your actual sheet ID Find this in your Google Sheets URL: https://docs.google.com/spreadsheets/d/[SHEET_ID]/edit Replace YOUR_SHEET_NAME with your worksheet name (e.g., "Sheet1" or "Form Responses 1") MailChimp Settings: Open the "Add to MailChimp" node Replace YOUR_MAILCHIMP_LIST_ID with your audience ID Find this in MailChimp: Audience → Settings → Audience name and defaults Verify the status is set to "subscribed" Google Sheets Format Requirements Your Google Sheet must have the following columns (exact names): Names**: Full name of the contact (e.g., "John Doe") Email address**: Valid email address Phone Number**: Contact phone number (optional) Example: | Names | Email address | Phone Number | |-------|--------------|--------------| | John Doe | john@example.com | +1234567890 | | Jane Smith | jane@example.com | +0987654321 | How to Use Manual Execution: Open the workflow in n8n Click "Execute Workflow" Monitor the execution progress Check the output of "Create Import Summary" for results Scheduling (Optional): To run this automatically: Replace the "Manual Trigger" node with a "Schedule Trigger" node Set your desired schedule (e.g., daily at 9 AM) Activate the workflow Customization Options Adding More Fields: To include additional fields like company name or address: Add columns to your Google Sheet Modify the "Edit Fields" node to include new fields Update the "Format Subscriber Data" code to map new fields Add corresponding merge fields in the MailChimp node Handling Duplicates: The workflow uses "continueRegularOutput" error handling, which means: Existing subscribers will be skipped New subscribers will be added The workflow continues processing Adding Email Notifications: To receive import summaries via email: Add a Gmail or Email node after "Create Import Summary" Configure with your email settings Use the import summary data in the email body Troubleshooting Common Issues: "Invalid API Key" (MailChimp) Verify your API key is correct Check that your MailChimp account is active "Sheet not found" (Google Sheets) Verify the sheet ID is correct Ensure the service account has access to the sheet "Email already exists" errors This is normal for existing subscribers The workflow will continue processing other contacts Missing data in MailChimp Check that column names match exactly (case-sensitive) Verify data exists in the Google Sheet Best Practices Test First: Always test with a small dataset first Backup Data: Export your MailChimp list before large imports Clean Data: Ensure email addresses are valid before importing Monitor Regularly: Check import summaries for any issues Respect Privacy: Only import contacts who have consented to receive emails Support For issues specific to: n8n platform: Visit n8n Community Forum Google Sheets API: Check Google Developers Documentation MailChimp API: See MailChimp API Documentation Need help customizing? Contact me for consulting and support or add me on LinkedIn - https://www.linkedin.com/in/femi-adedayo-h44/ License This workflow template is provided free for personal and commercial use. Feel free to modify and share!

This workflow restores all n8n instance workflows from GitHub backups using the n8n API node. It complements the Backup Your Workflows to GitHub template by allowing users to seamlessly restore previously saved workflows. How It Works The workflow fetches workflows stored in a GitHub repository and imports them into your n8n instance. Setup Instructions To configure the workflow, update the Globals node with the following values: repo.owner** – Your GitHub username repo.name** – The name of your GitHub repository storing the workflows repo.path** – The folder path within the repository where workflows are stored For example, if your GitHub username is john-doe, your repository is named n8n-backups, and workflows are stored in a workflows/ folder, you would set: repo.owner → john-doe repo.name → n8n-backups repo.path → workflows/ Required Credentials GitHub API** – Access to your repository n8n API** – To import workflows into your n8n instance Who Is This For? This template is ideal for users who want to restore their workflows from GitHub backups, ensuring easy migration and recovery in case of data loss. Check out my other templates: 👉 My n8n Templates

🤖🥗 Telegram Nutrition AI Assistant (Alternative to Cal AI App) > AI-powered nutrition assistant for Telegram — log meals, set goals, and get personalized daily reports with Google Sheets integration. 📋 Description This n8n template creates a Telegram-based Nutrition AI Assistant 🥑🔥 designed as an open-source alternative to the Cal AI mobile app. It allows users to interact with an AI agent via text, voice, or images to track meals, calculate macros, and monitor nutrition goals directly from Telegram. The system integrates Google Sheets as the database, handling both user profiles and meal logs, while leveraging Gemini AI for natural conversation, food recognition, and daily progress reports. ✨ Key Features 💬 Multi-input support: Text, voice messages (transcribed), and food images (AI analysis). 📊 Macro calculation: Automatic estimation of calories, proteins, carbs, and fats. 📝 User-friendly registration: Simple onboarding without storing personal health data (no weight/height required). 🎯 Goal tracking: Users can set and update calorie and protein targets. 📈 Daily reports: Personalized progress messages with visual progress bars. 🗂 Google Sheets integration: Profile table for user targets. Meals table for food logs. 🔄 Advanced n8n nodes: Includes use of Merge, Subworkflow, and Code nodes for data processing and report generation. 💡 Acknowledgment Inspired by the Cal AI concept 💡 — this template demonstrates how to reproduce its main functionality with n8n, Telegram, and AI agents as a flexible, open-source automation workflow. 🏷 Tags telegram ai-assistant nutrition meal-tracking google-sheets food-logging voice-transcription image-analysis daily-reports n8n-template merge-node subworkflow-node code-node telegram-trigger google-gemini 💼 Use Case Use this template if you want to: 🥗 Log meals using text, images, or voice messages. 📊 Track nutrition goals (calories, proteins) with daily progress updates. 🤖 Provide a chat-based nutrition assistant without building a full app. 🗂 Store structured nutrition data in Google Sheets for easy access and analysis. 💬 Example User Interactions 📸 User sends a photo of a meal → AI analyzes the food and logs calories/macros. 🎤 User sends a voice message → AI transcribes and logs the meal. ⌨️ User types “report” → AI returns a daily nutrition summary with progress bars. 🥅 User says “update my protein goal” → AI updates profile in Google Sheets. 🔑 Required Credentials Telegram Bot API (Bot Token) Google Sheets API credentials AI Provider API (Google Gemini or compatible LLM) ⚙️ Setup Instructions 🗂 Create two Google Sheets tables: Profile: User_ID, Name, Calories_target, Protein_target Meals: User_ID, Date, Meal_description, Calories, Proteins, Carbs, Fats 🔌 Configure the Telegram Trigger with your bot token. 🤖 Connect your AI provider credentials (Gemini recommended). 📑 Connect Google Sheets with your credentials. ▶️ Deploy the workflow in n8n. 🎯 Start interacting with your nutrition assistant via Telegram. 📌 Extra Notes 🟩 Green section: Handles Telegram trigger and user check. 🟥 Red section: Registers new users and sets goals. 🟦 Blue section: Processes text, voice, and images. 🟨 Yellow section: Generates nutrition reports. 🟪 Purple section: Main AI agent controlling tools and logic. 💡 Need Assistance? If you’d like help customizing or extending this workflow, feel free to reach out: 📧 Email: johnsilva11031@gmail.com 🔗 LinkedIn: John Alejandro Silva Rodríguez

Purpose The purpose of this automation is to help context switch from office to some side projects or passion gigs so you can be free of distracting thoughts and re-set your perspective. Benefits Anyone who works full time and also does something on the side (perhaps a side gig/being a mom/just follow your passion project) What you need N8N (lol) Any LLM API Key (I used OpenAI 4.1) IPhone (automations and shortcuts) Template Setup Setup LLM API key. Import template file to new workflow. On Iphone create a new shortcut as per video. Create automation steps. Resources Youtube

Automatically detect new n8n releases (stable or beta) from GitHub, update Coolify environment variables, and trigger deployments. Functionality This workflow automates deployment of n8n releases to a Coolify instance. It supports two tracks: Beta Releases: Checks GitHub every minute for prereleases, filters duplicates, updates the N8N_VERSION environment variable, and deploys. Stable Releases (disabled by default): Checks the latest stable release hourly and deploys. Key Features: Deduplication**: Ensures no repeated deployments for the same release. Version Parsing**: Extracts the semantic version (e.g., 1.34.0) from GitHub release names. Coolify Integration**: Updates environment variables and triggers deployments via API. Expected Outcomes New n8n beta/stable releases detected via GitHub API. Coolify environment variable N8N_VERSION updated to the latest version. Automatic deployment triggered in Coolify. Setup Guide Replace Placeholders: Update m8ccg8k44coogsk84swk8kgs in the Update ENV and Deploy nodes with your Coolify Application UUID. Configure Credentials: Add Coolify API credentials (httpHeaderAuth) with a valid API token in the headers. Enable Triggers: Toggle the Auto Update Latest Release node if stable releases are desired. Adjust schedule intervals as needed. Test: Run the workflow manually to validate API connections and version parsing. SEO Keywords Automated Deployment, n8n CI/CD, Coolify Integration, GitHub Release Monitoring, Environment Variable Management, Beta Release Automation.

A lightweight no-code workflow that captures student check-in data via a mobile app or webhook, stores it in a Google Sheet, and instantly notifies the class teacher via email. 🎯 What This Does Students check in using a mobile app or QR code Their data is formatted and saved to a Google Sheet A notification email is sent to the class teacher in real time 🔧 Workflow Steps | Step | Description | | ------------------------------ | ----------------------------------------------------------- | | Student Check-in (Webhook) | Triggered via POST request from mobile app or QR scanner | | Format Data | Cleans and prepares incoming JSON into structured format | | Append or Update Row | Saves student check-in data into Google Sheets | | Email Teacher | Sends formatted check-in email to the class teacher | | Success Response | Returns a confirmation response to the mobile app or system | 📱 Example Check-in Input (Webhook Body) { "student_name": "Aarav Mehta", "student_id": "STU025", "class_name": "Grade 6B" } 📊 Google Sheets Format | Student Name | Student ID | Class | Date | Time | | ------------ | ---------- | -------- | ---------- | ----- | | Aarav Mehta | STU025 | Grade 6B | 2025-08-06 | 08:35 | Date and time are added dynamically in the workflow. ⚙️ Setup Requirements n8n Instance** – Deployed with public webhook support Google Sheets** – Sheet with columns as shown above Email SMTP Settings** – For sending teacher notification ✅ Quick Setup Instructions Import the workflow into your n8n instance Replace the webhook URL in your mobile app Set your Google Sheet ID and range Enter the teacher’s email in the “Email Teacher” node Test with mock data Deploy and use live!

How it works This workflow changes the file name, and therefore the extension and MIME type, of any binary file passed to it. This is perfect for converting file formats on the fly, like turning a Telegram voice message (.oga) into an MP3 for an AI transcription service. Set New File Name: The SET OUTPUT FILE NAME node is where you define the desired output file name and extension (e.g., audio.mp3). It also dynamically captures the property name of the incoming binary (e.g., data). Extract Binary Data: The workflow temporarily converts the binary file into a Base64 text string to make it accessible in the next step. Rebuild Binary with New Name: A Code node takes the Base64 data and reconstructs it as a binary file, but this time, it assigns the new file name you specified. n8n automatically sets the MIME type based on the new file extension. Set up steps Setup time: < 1 minute This workflow is designed to be used as a sub-workflow. In your main workflow, add an Execute Sub-Workflow node where you need to change a file's type. In the Workflow parameter, select this "Change Binary MimeType/Extension" workflow. Open this workflow and go to the SET OUTPUT FILE NAME node. Modify the output_file_name value to your desired file name (e.g., voice_message.mp3 or document.pdf). Save this workflow. Now, any binary file you send to it from your main workflow will be returned with the new fileName and mimeType.

Overview This workflow provides Retell agent builders with a simple way to populate dynamic variables using n8n. The workflow fetches user information from a Google Sheet based on the phone number and sends it back to Retell. It is based on Retell's Inbound Webhook Call. Retell is a service that lets you create Voice Agents that handle voice calls simply, based on a prompt or using a conversational flow builder. Who is it for For builders of Retell's Voice Agents who want to make their agents more personalized. Prerequisites Have a Retell AI Account Create a Retell agent Purchase a phone number and associate it with your agent Create a Google Sheets - for example, make a copy of this one. Your Google Sheet must have at least one column with the phone number. The remaining columns will be used to populate your Retell agent’s dynamic variables. All fields are returned as strings to Retell (variables are replaced as text) How it works The webhook call is received from Retell. We filter the call using their whitelisted IP address. It extracts data from the webhook call and uses it to retrieve the user from Google Sheets. It formats the data in the response to match Retell's expected format. Retell uses this data to replace dynamic variables in the prompts. How to use it See the description for screenshots! Set the webhook name (keep it as POST). Copy the Webhook URL (e.g., https://your-instance.app.n8n.cloud/webhook/retell-dynamic-variables) and paste it into Retell's interface. Navigate to "Phone Numbers", click on the phone number, and enable "Add an inbound webhook". In your prompt (e.g., "welcome message"), use the variable with this syntax: {{variable_name}} (see Retell's documentation). These variables will be dynamically replaced by the data in your Google Sheet. Notes In Google Sheets, the phone number must start with '+. Phone numbers must be formatted like the example: with the +, extension, and no spaces. You can use any database—just replace Google Sheets with your own, making sure to keep the phone number formatting consistent. 👉 Reach out to us if you're interested in analysing your Retell Agent conversations.

An automated backup solution designed for self-hosted n8n users to automatically backup their workflows to Bitbucket, leveraging Bitbucket's free private repository offering. Perfect for maintaining version control of your n8n workflows without additional costs. How it works: Runs on a regular schedule to check all workflows in your n8n instance Compares each workflow with its version in Bitbucket Only uploads workflows that are new or have changed Uses basic rate limiting to stay within Bitbucket's API limits Formats filenames for easy tracking and includes timestamps in commit messages Handles errors gracefully with automatic retries Set up steps (10-15 minutes): Create a free Bitbucket account and private repository Create a Bitbucket App Password with repository write access Add Bitbucket credentials to n8n (using your username and app password) Set up n8n API access (generate API key in your n8n instance) Configure your Bitbucket workspace and repository names in the Set node Optional: Adjust the backup schedule (default: 2 AM daily) Perfect for n8n self-hosters who want: Version control for their workflows Automated daily backups Free private repository storage Easy workflow recovery Change tracking over time The workflow includes basic error handling and rate limiting to ensure reliable backups even with larger numbers of workflows. Adjust your timing based on https://support.atlassian.com/bitbucket-cloud/docs/api-request-limits/.

This n8n workflow automates personalized travel assistance via WhatsApp through a friendly virtual agent named Alex. It helps users plan trips, explore destinations, get visa/weather/hotel information, and book packages—all through a conversational interface. The system ensures quick, human-like support 24/7, improving customer experience and reducing manual handling by travel agents. Key Features The Travel Assistant agent provides contextual responses based on conversation history stored in memory. Alex maintains a friendly, professional tone throughout all interactions to enhance user experience. The workflow includes intelligent waiting mechanisms to ensure proper response processing. Memory functionality allows for seamless continuation of conversations across multiple interactions. Workflow Process The Get WhatsApp Message node captures incoming messages from users on WhatsApp, initiating the travel assistance process. The Travel Assistant node processes user queries using AI to understand travel needs and generate appropriate responses for trip planning, destination information, visa requirements, weather updates, and booking assistance. The Travel Plan Creator agent works in conjunction with the main assistant to generate detailed itineraries and travel recommendations based on user preferences. The Memory node stores conversation context and user preferences, enabling personalized responses and seamless conversation flow across multiple interactions. The Wait For Response node introduces intelligent delays to ensure proper message processing and natural conversation pacing. The Send Reply On WhatsApp node delivers the AI-generated travel assistance back to the user through WhatsApp messaging. Setup Instructions Import the workflow into n8n and configure WhatsApp Business API credentials for message handling. Set up the AI service for the Travel Assistant and Travel Plan Creator agents with your preferred language model. Configure the Memory node with appropriate storage settings for conversation persistence. Test the workflow by sending various travel-related queries through WhatsApp to ensure proper responses. Monitor conversation quality and adjust AI parameters as needed for optimal user experience. Prerequisites WhatsApp Business API access or WhatsApp integration service AI/LLM service for travel assistance (OpenAI, Anthropic, or similar) Database or storage service for conversation memory Access to travel data APIs for real-time information (weather, visa requirements, hotel availability) Modification Options Modify the Travel Assistant node to include specific travel databases, local recommendations, or branded responses. Adjust the conversation memory settings to control how much context is retained across interactions. Customize the Travel Plan Creator to include preferred booking platforms, hotel chains, or travel partners. Add additional specialized agents for specific travel services like flight booking, car rentals, or activity reservations. Configure response timing in the Wait For Response node to match your desired conversation flow.

What this does Show you how to us XMLRPC APIs via the generic HTTP-Request-node, by the example of posting to a wordpress blog This is also a feasible workaround if a specific n8n integration does not work or stops working (which happens e.g. with the Wordpress node) How it works First, the XML payload for the request is being prepared (in a code node, which also properly escapes special character in the values that you want to send to the XMLRPC endpoint) Then, the HTTP Request node sends the request using the HTTP post method Last, the returned XML response is converted to JSON which a conditional node uses to determine whether th operation was successful or not Setup steps: Import workflow Ensure you have a wordpress blog with a user that has an app-Password Edit the "Settings"-node and enter your individual values for url/user/app-pw