Workflow Templates

Slack Bot n8n Integration Hub - Workflow Submission 🚀 Showcase: Endless Possibilities with n8n Integration This repository demonstrates a powerful Slack Bot Socket App that seamlessly integrates with n8n for automation workflows. This is just a showcase of what's possible when combining Slack's interactive capabilities with n8n's automation power - the possibilities are truly endless! 📋 Project Overview Repository: slack-n8n-integration-hub Status: ✅ Committed and Ready for Submission This project showcases how to create seamless interactions between Slack users and n8n workflows, demonstrating: Real-time Data Submission** from Slack to n8n workflows Interactive Approval/Rejection** workflows triggered from Slack Secure Webhook Communication** with optional Basic Authentication Dynamic Modal Interactions** with immediate feedback Error Handling and User Experience** optimization 🎯 Key Features Demonstrated 1. Data Input Integration Users can submit custom data directly from Slack Data is instantly sent to n8n workflows for processing Real-time feedback and confirmation messages 2. Approval Workflow Automation Interactive approve/reject buttons in Slack modals Decisions trigger different n8n workflow paths Automated decision logging and processing 3. Enhanced User Experience Modal closes automatically after actions Submit button positioned below input for better UX Comprehensive error handling and user feedback 4. Security & Authentication Optional HTTP Basic Auth for webhook security Environment-based configuration management Secure credential handling 🔧 Technical Implementation Slack Bot Features: Socket Mode for real-time communication Custom slash commands (/automation) Interactive modals with dynamic content Button actions and form submissions n8n Integration: Webhook triggers for data reception Structured payload formats Authentication support Error handling and response management Workflow Payload Examples: Data Submission: { "type": "data_submission", "data": "User input data here", "user": { "id": "U1234567890", "name": "username" }, "timestamp": "2024-01-01T12:00:00.000Z", "source": "slack_bot" } Approval Action: { "type": "approval_action", "action": "approve", "user": { "id": "U1234567890", "name": "username" }, "timestamp": "2024-01-01T12:00:00.000Z", "source": "slack_bot" } 🌟 Why This Matters for n8n Community This project demonstrates how n8n can be the backbone for: Human-in-the-loop** automation workflows Interactive approval** processes Real-time data collection** from team communication tools Seamless integration** between chat platforms and automation Scalable workflow triggers** from multiple sources 🚀 Endless Possibilities This is just the beginning! With this foundation, you can build: IT Service Desk** automation with Slack approvals Content Publishing** workflows with team reviews Data Collection** and processing pipelines Incident Management** with automated escalations Project Management** with status updates and approvals Customer Support** ticket routing and responses DevOps Deployments** with approval gates Financial Approvals** with audit trails HR Processes** with automated workflows Marketing Campaigns** with content approvals 📁 Repository Structure slack-n8n-integration-hub/ ├── app.js # Main Slack Bot application ├── package.json # Dependencies and scripts ├── .env.example # Environment configuration template ├── README.md # Complete setup documentation ├── CONTRIBUTING.md # Contribution guidelines ├── Slack_Bot_n8n_Integration_Hub.json # n8n workflow export ├── n8n-workflow-examples.json # Additional workflow examples └── test-webhook.js # Webhook testing utilities 🎉 Ready for n8n Community This workflow is: ✅ Fully Tested and working ✅ Well Documented with setup instructions ✅ Open Source and ready for community use ✅ Extensible for various use cases ✅ Production Ready with error handling 🔗 Get Started Clone the repository: git clone https://github.com/iam-niranjan/slack-n8n-integration-hub.git Follow the setup guide in the main README.md Import the n8n workflows from the JSON files Customize for your use case and explore the possibilities! This showcase demonstrates that with n8n and Slack integration, the automation possibilities are truly endless! 🚀 Ready to submit to n8n community for sharing and collaboration.

This n8n workflow automates the assignment of existing users to organizations in Zammad based on their email domains, utilizing Zammad’s "domain-based assignment" feature. Use Case Automate the post-hoc assignment of existing users to organizations in Zammad by leveraging their email domains. This ensures efficient management of user-organization relationships using Zammad’s "domain-based assignment" feature. Requirements An active Zammad account with API access. Existing users and organizations in Zammad with proper email and domain configurations. Zammad organizations must have domain-based assignment enabled. Credentials Set up your Zammad API credentials in n8n to allow the workflow to interact with your Zammad instance securely. If you have found an error or have any suggestions, please report them here on Github.

The Sound Effects Generator is an automated workflow that allows users to create realistic sound effects using AI and save them directly to Google Drive. It generates high-quality sound effects (up to 30 seconds long) based on user prompts. How It Works: User Input via Web Form A form is presented to the user asking for: A prompt describing the sound (e.g. "waves crashing", "laser blast"). A duration in seconds (up to 30 seconds). API Request to Generate Audio The input is sent to CassetteAI via a POST request using API with proper authentication. Status Polling The workflow waits for 10 seconds and then checks the status of the request. Conditional Flow If the audio generation is complete (COMPLETED), it proceeds to fetch the audio file URL. If not, it waits and retries. Download & Save The audio file is downloaded from the URL. It is automatically uploaded to a specific folder in the user’s Google Drive, with a timestamped filename. Key Advantages Fast & Efficient**: Generates up to 30 seconds of audio in just 1 second of processing time. No Coding Required**: Entire flow can be triggered via a simple form interface. Automated Storage**: Files are automatically saved to a preconfigured Google Drive folder. Scalable**: Can be reused for multiple projects by simply changing the input prompts. Secure**: Uses secure API key-based authentication for interaction with Fal.run and Google Drive. Customizable**: Easy to adapt or extend—for example, sending download links via email or Telegram. How It Works Form Submission: The workflow starts with a form where users input a prompt and the desired duration (max 30 seconds) for the sound effect. Audio Creation: The submitted data is sent to the CassetteAI Sound Effects Generator API via an HTTP request, which initiates the sound effect generation process. Status Check: The workflow periodically checks the status of the request. If the status is "COMPLETED," it proceeds to fetch the audio file. Audio Retrieval: The generated audio file is downloaded from the provided URL and uploaded to a specified Google Drive folder, with a timestamped filename for organization. Set Up Steps API Key Configuration: Create an account on fal.ai and obtain an API key. In the "Create audio" node, set the "Header Auth" with: Name: Authorization Value: Key YOURAPIKEY (replace YOURAPIKEY with your actual API key). Google Drive Integration: Ensure the Google Drive node is configured with the correct OAuth2 credentials and folder ID. Adjust the folder ID in the "Upload Audio" node if a different destination is preferred. Need help customizing? Contact me for consulting and support or add me on Linkedin.

This workflow demonstrates how to use currentRunIndex to get the running index. Function node: This node generates mock data for the workflow. Replace it with the node whose data you want to split into batches. SplitInBatches node: This node splits the data with the batch size equal to 1. Based on your use-case, set the value of the Batch Size. IF node: This node checks the running index. If the running index equals 5 the node returns true and breaks the loop. The node uses the expression {{$node["SplitInBatches"].context["currentRunIndex"];}}, which returns the running index. Set node: This node prints a message Loop Ended. Based on your use-case, connect the false output of the IF node to the input of the node you want to execute if the condition is false.

Who is this for? For developers and organizations that need to convert DOCX files to PDF. What problem is this workflow solving? The file format conversion problem. What this workflow does Downloads the DOCX file from the web. Converts the DOCX file to PDF. Stores the PDF file in the local file system. How to customize this workflow to your needs Open the HTTP Request node. Adjust the URL parameter (all endpoints can be found here). Add your secret to the Query Auth account parameter. Please create a ConvertAPI account to get an authentication secret. Adjust url_to_file in the Config node to URL pointing to your file. Optionally, additional Body Parameters can be added for the converter.

Automated Execution Pruning This workflow is designed to help you manage and optimize your n8n instance by automatically pruning old workflow executions, ensuring a cleaner environment and improved performance. You can customize the retention period to suit your needs. Key Features: Configurable Retention Period: The workflow is preconfigured to delete workflow executions older than 10 days. You can easily adjust this duration by modifying the condition in the If node. Daily Automation: Using the Schedule Trigger, the workflow runs daily at the specified time (default: 4:44 AM), retrieving all workflow executions and identifying those that are older than the defined retention period. On-Demand Testing: The Manual Trigger allows you to test the workflow at any time, ensuring everything is working as expected. Decision Making: The If node evaluates each execution based on its start date and determines whether it should be deleted or retained. Execution Pruning: Delete Action: Executions meeting the criteria are removed via the Delete Execution node. No-Operation: Executions that don't meet the criteria remain untouched. Workflow Nodes: Manual Trigger: Enables on-demand testing of the workflow. Schedule Trigger: Runs the workflow daily at the configured time. n8n List Execution: Fetches all executions in your n8n instance. If Node: Compares the execution's start date with the configured retention period. Delete Execution: Deletes executions older than the specified retention period. No Operation: Serves as a placeholder for executions that don't meet the pruning criteria. How to Customize: Retention Period**: Update the If node's condition to modify the retention period. For instance, change 10 * 24 * 60 * 60 * 1000 to the desired number of days in milliseconds. Schedule**: Adjust the timing of the Schedule Trigger to match your preferred automation schedule. This workflow ensures your instance remains efficient by keeping only the relevant execution logs. Use it to maintain a streamlined and clutter-free environment effortlessly.

This workflow allows you to check the To-Do list on Notion and send a message on Slack. Prerequisites Create a Notion page similar to this page. Create credentials for Notion by following the instructions mentioned in the documentation. Follow the steps mentioned in the documentation to create credentials for Slack. Cron node: This node triggers the workflow every day. Notion node: This node fetches all the tasks from Notion. IF node: This node checks if the task is assigned to a particular user. Create a Direct Message: This node will create a direct message channel with the user. Send a Direct Message: This node will send the to-do lists in the direct message. NoOp: This node is connected to the false output of the IF node. If the condition is false, no further action will be taken.

Problem Teams often struggle with email overload, leading to missed actions and inefficient meeting preparation. Solution This workflow automates email management using n8n and AI. It fetches emails, summarizes key points and actions, and sends two concise updates—one in the morning and one at night. How It Works Triggers at 7 AM and 9 PM: Automates the process to summarize emails received during specific time blocks. Fetches Emails: Retrieves emails from the last 24 hours or after a specific time. Summarizes with AI: Uses OpenAI to process the email content into actionable summaries. Sends Team Updates: Compiles the summaries into a concise, formatted email and sends it to the team. Expected Results Significant reduction in missed actions and follow-ups. Customizations Adjust timings, filters, and recipients to suit your team’s needs.

> This has been updated to support the Query feature added to the Zendesk node in 0.144.0 This workflow will post all New and Open tickets without an agent assigned to a Slack channel on a schedule. The function node is used in this example to merge multiple inputs into one output message which is then used as the Slack message. The output in Slack will be similar to the below message, The "TICKET_ID" will be a link to the ticket. > Unassigned Tickets TICKET_ID [STATUS] - TICKET_SUBJECT Usage Update the Cron schedule, The default value is 16:30 daily. Update the Credentials in the Zendesk nodes Update the Credentials and Channel in the Slack Node Grab a coffee and enjoy! Zendesk Query In the Zendesk node we are using the query assignee:none status<pending this returns all New and Open tickets with no assignee allowing us to remove the extra nodes.

What it does This is a simplistic demo workflow showing how to extract a license plate number from an image of a car submitted via a form – or in more general terms showcasing how you can: use a form trigger to upload files and feed it into an LLM use a changeable LLM model for image-to-text analysis Set up steps Import the workflow Ensure you have registered and account, purchased some credits and created and API key for OpenRouter.ai Create/adapt the OpenRouter credential with your indivial API key for OpenRouter "Test workflow" and submit an image of a car with license plate to extract its number How to adapt By changing the "prompt" in th "Settings" node you can quickly adapt this exemplatory workflow to other image-to-text use cases, such as: summarization: "summarize what's seen in the image" location finding: "identify the location where the image was taken" text extraction: "extract all text from the image and return it as markdown" Thanks to using OpenRouter, you also can quickly experiment with finding good model choices by simply changing the "model" in the "Settings" node. The following models gave good results for this demo use-case: google/gemini-2.0-flash-001 meta-llama/llama-3.2-90b-vision-instruct openai/gpt-4o The llama-3.2-11b and even claude-3.5-sonnet didn't recognize all characters in all test images. Using a generic LLM-model offers a quick way of prototyping an image-to-text application. For specific use cases in serious and scalable production deployments, consider using an API based service specifically made to that purpose, such as: Google Cloud Vision API Microsoft Azure Computer Vision Azure AI Document Intelligence Amazon Textract

Let a user load multiple files with a Form node, and process the binary data. A very important workflow for many tools. This is a learning example of several core concepts that are hard to grasp in n8n: $binary data Loop and $runIndex Split Out The Save File deomonstrates how to access the binary data correctly, but could be swapped to POST the files to an AI, for example.

This n8n workflow monitors email alerts for disk utilization exceeding 80%, extracts the server IP, logs into the server, and purges logs from Nginx, PM2, Docker, and system files to clear disk space. Key Insights Ensure email alerts are consistently formatted with server IP details. SSH access must be properly configured to avoid authentication failures. Workflow Process Initiate the workflow with the Check Disk Alert Emails node when an email triggers on high disk usage. Parse the email to extract the server IP using the Extract Server IP from Email node. Set up SSH credentials and paths manually with the Prepare SSH Variables node. Execute cleanup commands to delete logs from Nginx, PM2, Docker, and system files using the Run LogCleanup Commands via SSH node. Usage Guide Import the workflow into n8n and configure email and SSH credentials. Test with a sample email alert to verify IP extraction and log deletion. Prerequisites Email service (e.g., IMAP or API) for alert monitoring SSH access with valid credentials Customization Options Modify the Prepare SSH Variables node to target specific log directories or adjust cleanup commands for different server setups.