Workflow Templates

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Overview This workflow automates the process of transcribing audio files and summarizing them using OpenAI models, with the final output stored neatly in Notion. Whether you're a researcher, content creator, student, or professional, this automation saves time by converting voice recordings into actionable summaries with zero manual effort. Created by: Abdullah Dilshad Contact: iamabdullahdilshad@gmail.com Who It’s For This template is ideal for: Researchers**: Transcribe and summarize interviews, lectures, or research recordings. Content Creators**: Convert podcasts or videos into transcripts and social captions/show notes. Students**: Automatically turn lectures or study group audio into summarized notes. Professionals**: Log meeting notes and summaries directly into your Notion workspace. How It Works This four-step workflow performs the following: Step 1:* *Trigger: New Audio in Google Drive** Automatically triggers when a new audio file (MP3/WAV) is uploaded to a specified Google Drive folder.The file is then downloaded for processing. Step 2: Transcribe Audio with Whisper** The audio file is sent to OpenAI’s Whisper model for high-accuracy transcription. Step 3: Summarize Transcript with GPT-4** The transcript is passed to GPT-4, which generates a clean, concise summary. Step 4: Store Summary in Notion** A new Notion page is created with the generated summary and optional metadata (file name, upload time, etc.). Setup Instructions Step 1: Google Drive Trigger** Connect your Google Drive account. Select the folder you want to monitor. This node detects new file uploads and passes the file for download. Step 2: Download File** Downloads the new audio file for transcription. Step 3: Transcribe Recording (OpenAI Whisper) Connect your OpenAI API Key. Ensure this node receives the binary audio file. It will return the transcription as plain text. Step 3: Transcribe Recording (OpenAI Whisper)** Connect your OpenAI API Key. Ensure this node receives the binary audio file. It will return the transcription as plain text. Step 4: Summarize Transcript (GPT-4 via AI Agent)** Use your OpenAI API Key. Configure a summarization prompt like: "Summarize the following transcript in a clear and concise manner:" Connect the output from Whisper into this GPT-4 prompt. Step 5: Notion Integration** Connect your Notion account. Choose or create a database to store summaries. Map the GPT output (summary) to a "Text" or "Rich Text" property. Optionally include metadata like filename, file upload date, etc.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automatically transform your video uploads into AI-powered summaries with key topic extraction and instant team notifications. What this workflow does Monitors Google Drive for new video uploads Downloads and processes videos using VLM Run AI Generates intelligent summaries with key topics extracted Posts results to Slack for immediate team access Setup Prerequisites: Google Drive account, VLM Run API credentials, Slack workspace, self-hosted n8n. You need to install VLM Run community node Quick Setup: Configure Google Drive OAuth2 and create video upload folder Add VLM Run API credentials Set up Slack integration for notifications Update folder/channel IDs in workflow nodes Test and activate Perfect for Meeting recordings and training videos Webinar summaries and educational content Content analysis and team collaboration Any video content requiring quick insights Key Benefits Asynchronous processing** handles large files without timeouts Multi-format support** for MP4, AVI, MOV, WebM, MKV Instant team updates** via Slack notifications Saves hours** of manual video review time How to customize Extend by adding: Video categorization and tagging Integration with project management tools Email notifications alongside Slack Searchable video databases with summaries This workflow transforms lengthy videos into actionable insights, making your content instantly accessible and shareable with your team.

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

Who this is for? Extract Amazon Best Seller Electronic Info is an automated workflow that extracts best seller data from Amazon's Electronics section using Bright Data Web Unlocker, transform it into structured JSON using Google Gemini's LLM, and forwards a fully structured JSON response to a specified webhook for downstream use. This workflow is tailored for: eCommerce Analysts** Who need to monitor Amazon best-seller trends in the Electronics category and track changes in real-time or on a schedule. Product Intelligence Teams** Who want structured insights on competitor offerings, including rankings, prices, ratings, and promotions. AI-powered Chatbot Developers** Who are building assistants capable of answering product-related queries with fresh, structured data from Amazon. Growth Hackers & Marketers** Looking to automate competitive research and surface trending product data to inform pricing strategies. Data Aggregators and Price Trackers** Who need reliable and smart scraping of Amazon data enriched with AI-driven parsing. What problem is this workflow solving? Keeping up with Amazon's best sellers in Electronics is a time-consuming, error-prone task when done manually.This workflow automates the process, ensuring:​ Automating Data Extraction from Amazon Best Sellers using Bright Data, ensuring reliable access to real-time, structured data. Enhancing Raw Data with Google Gemini, turning product lists into structured JSON using the Google Gemini LLM. Sending Results to a Webhook, enabling seamless integration into dashboards, databases, or chatbots. What this workflow does The workflow performs the following steps:​ Extracts Amazon Best Seller Electronics page info using Bright Data's Web Unlocker API. Processes the unstructured content using Google Gemini's Flash Exp model to extract structured product data. Sends the structured information to a webhook endpoint. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Amazon URL with the Bright Data zone by navigating to the Amazon URL with the Bright Data Zone node. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. How to customize this workflow to your needs This workflow is built to be flexible - whether you're a market researcher, e-commerce entrepreneur, or data analyst. Here's how you can adapt it to fit your specific use case: Change the Amazon Category** Update the Amazon URL with the topic of your interest such as Computers & Accessories, Home Audio, etc. Customize the Gemini Prompt** Update the Gemini prompt to get different styles of output — comparison tables, summaries, feature highlights, etc. Send Output to Other Destinations** Replace the Webhook URL to forward output to: Google Sheets Airtable Slack or Discord Custom API endpoints

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.

This n8n template demonstrates how to add a document conversion process to incoming Word documents in a OneDrive folder. Documents are converted to PDF and emailed to a reviewer. Use cases would be environments where incoming documents are dropped into cloud storage and a human needs to review them. By converting to PDF, it becomes easier to read in a consistent format in the browser. How it works Listen for new files added in a OneDrive folder, identified by an ID Download the bits of the new document if the file was a Micrsoft Word document (the API I'm using can convert any Office document, but wanted to start simple) Upload to Foxit's API service, convert to PDF, and download when done Use GMail to mail the PDF to a human reviewer. How to use You'll need to determine a OneDrive folder ID to monitor, or select an entire account instead, just be careful when testing. When the workflow is done, it emails to myself, so please connect your own GMail and set a preferred email address for testing. Requirements A Microsoft OneDrive account Foxit developer account (https://developer-api.foxit.com) A Gmail account At least one Word document - we all have that, right? Next Steps This workflow could be modified to work with any Office style document, and could also upload the PDF version back to OneDrive.

Template Description This n8n workflow template allows you to create a masked email address using the Fastmail API, triggered by a webhook. This is especially useful for generating disposable email addresses for privacy-conscious users or for testing purposes. Workflow Details: Webhook Trigger: The workflow is initiated by sending a POST request to a specific webhook. You can include state and description in your request body to customize the masked email's state and description. Session Retrieval: The workflow makes an HTTP request to the Fastmail API to retrieve session information. It uses this data to authenticate further requests. Create Masked Email: Using the retrieved session data, the workflow sends a POST request to Fastmail's JMAP API to create a masked email. It uses the provided state and description from the webhook payload. Prepare Output: Once the masked email is successfully created, the workflow extracts the email address and attaches the description for further processing. Respond to Webhook: Finally, the workflow responds to the original POST request with the newly created masked email and its description. Requirements: Fastmail API Access**: You will need valid API credentials for Fastmail configured with HTTP Header Authentication. Authorization Setup**: Optionally set up authorization if your webhook is exposed to the internet to prevent misuse. Custom Webhook Request**: Use a tool like curl or create a shortcut on macOS/iOS to send the POST request to the webhook with the necessary JSON payload, like so: curl -X POST -H 'Content-Type: application/json' https://your-n8n-instance/webhook/87f9abd1-2c9b-4d1f-8c7f-2261f4698c3c -d '{"state": "pending", "description": "my mega fancy masked email"}' This template simplifies the process of integrating masked email functionality into your projects or workflows and can be extended for various use cases. Feel free to use the companion shortcut I've also created. Please update the authorization header in the shortcut if needed. https://www.icloud.com/shortcuts/ac249b50eab34c04acd9fb522f9f7068

Overview This workflow leverages the KIE. AI Veo3 model to generate AI videos from simple text descriptions. Users interact via a form interface, inputting a prompt (e.g., a scene description), and the system automatically submits the request to the KIE. AI API, monitors the generation status in real time, and retrieves the final video output. It's ideal for content creators, marketers, or developers exploring text-to-video AI creation, supporting intelligent video generation with minimal setup. Prerequisites A KIE. AI account and API key: Sign up at KIE.AI to obtain your free or paid API key. An active n8n instance (cloud or self-hosted) with HTTP Request and form submission capabilities. Basic knowledge of AI prompts for video generation to achieve optimal results. Setup Instructions Obtain API Key: Register at KIE. AI and generate your API key. Store it securely—do not share it publicly. Configure the Form: In the "On Form Submission" node, ensure fields like "prompt" (for video description) and "api_key" are set up. Example prompt: "A serene mountain landscape at sunset with birds flying." Test the Workflow: Click "Execute Workflow" in n8n. Access the generated form URL, submit your prompt and API key. The workflow will poll the API every 10 seconds until the video is ready, then display the results. Handle Outputs: The final node formats and displays the video file URL for download or embedding. Customization Tips Enhance Prompts**: Include specifics like duration, style (e.g., realistic, animated), actions, and visual elements to improve AI video quality. Keywords for SEO**: This template focuses on AI video generation, text-to-video models, Veo3 API integration, and automated workflows.

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.

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 workflow is designed to generate prompts for AI agents and store them in Airtable. It starts by receiving a chat message, processes it to create a structured prompt, categorizes the prompt, and finally stores it in Airtable. 2. Setup Instructions Prerequisites AI model eg Gemini, openAI etc** Airtable base and table or other storage tool** Step-by-Step Guide Clone the Workflow Copy the provided workflow JSON and import it into your n8n instance. Configure Credentials Set up the Google Gemini(PaLM) API account credentials. Set up the Airtable Personal Access Token account credentials. Map Airtable Base and Table Create a copy of the Prompt Library in Airtable. Map the Airtable base and table in the Airtable node. Customize Prompt Template Edit the 'Create prompt' node to customize the prompt template as needed. Configuration Options Prompt Template:** Customize the prompt template in the 'Create prompt' node to fit your specific use case. Airtable Mapping:** Ensure the Airtable base and table are correctly mapped in the Airtable node. 4. Running and Troubleshooting Running the Workflow Trigger the Workflow: Send a chat message to trigger the workflow. Monitor Execution: Use the n8n interface to monitor the workflow execution. Check Completion: Verify that the prompt is stored in Airtable and check the chat interface for the result. Troubleshooting Tips API Issues:** Ensure that the APIs and Airtable credentials are correctly configured. Data Mapping:** Verify that the Airtable base and table are correctly mapped. Prompt Template:** Check the prompt template for any errors or inconsistencies. Use Case Examples This workflow is particularly useful in scenarios where you want to automate the generation and management of AI agent prompts. Here are some examples: Rapid Prototyping of AI Agents: Quickly generate and test different prompts for AI agents in various applications. Content Creation:** Generate prompts for AI models that create blog posts, articles, or social media content. Customer Service Automation:** Develop prompts for AI-powered chatbots to handle customer inquiries and support requests. Educational Tools:** Create prompts for AI tutors or learning assistants. Industries/Professionals: Software Development:** Developers building AI-powered applications. Marketing:** Marketers automating content creation and social media management. Customer Service:** Customer service managers implementing AI-driven chatbots. Education:** Educators creating AI-based learning tools. Practical Value: Time Savings:** Automates the prompt generation process, saving significant time and effort. Improved Prompt Quality:** Leverages Google Gemini and structured prompt engineering principles to generate more effective prompts. Centralized Prompt Management:** Stores prompts in Airtable for easy access, organization, and reuse. 4. Running and Troubleshooting Running the Workflow:** Activate the workflow in n8n. Send a chat message to the webhook URL configured in the "When chat message received" node. Monitor the workflow execution in the n8n editor. Monitoring Execution:** Check the execution log in n8n to see the data flowing through each node and identify any errors. Checking for Successful Completion:** Verify that a new record is created in your Airtable base with the generated prompt, name, and category. Confirm that the "Return results" node sends back confirmation of the prompt in the chat interface. Troubleshooting Tips:** Error:** 400: Bad Request in the Google Gemini nodes: Cause:** Invalid API key or insufficient permissions. Solution:** Double-check your Google Gemini API key and ensure that the API is enabled for your project. Error:** Airtable node fails to create a record: Cause:** Invalid Airtable credentials, incorrect Base ID or Table ID, or mismatched column names. Solution:** Verify your Airtable API key, Base ID, Table ID, and column names. Ensure that the data types in n8n match the data types in your Airtable columns. Follow me on Linkedin for more

This workflow implements the Gemini AI chat model to summarize your daily meetings and send the summary to a Slack channel daily at 9 AM (or any other time you choose). It automatically retrieves your Google Calendar events and feeds them to the model. The workflow uses Google’s Gemini AI for response generation. How it works The workflow uses a Scheduled Trigger Node as the main trigger. The AI Agent Node uses the Google Calendar action to retrieve relevant meeting data. The AI Agent sends the retrieved information to the Google Gemini Chat Model (gemini-flash). The Google Gemini Chat Model generates a summary and informative response based on today’s meetings. ++Setup Steps++ Google Cloud Project and Vertex AI API: Create a Google Cloud project. Enable the Vertex AI API for your project. Google AI API Key: Obtain a Google AI API key from Google AI Studio. Credentials in n8n: Configure credentials in your n8n environment for: Google Gemini (PaLM) API (using your Google AI API key). Import the Workflow: Import this workflow into your n8n instance. Configure the Workflow: Update both Slack and Gemini nodes with your credentials.