Workflow Templates

This automated n8n workflow efficiently manages the setup, creation, and deletion of PostgreSQL and MySQL databases on a Linux server, executing tasks in approximately 10 seconds. It automates installation, configuration, and user management with support for remote access. Core Elements Set Parameters** - Defines server details, database type, action, and credentials Type Check** - Confirms the selected database type PostgreSQL Action Check** - Identifies the action for PostgreSQL PostgreSQL Create Check** - Validates creation conditions for PostgreSQL Install PostgreSQL** - Sets up and configures PostgreSQL Create PostgreSQL DB** - Establishes a new PostgreSQL database with user access Delete PostgreSQL DB** - Removes a PostgreSQL database and user MySQL Action Check** - Identifies the action for MySQL MySQL Create Check** - Validates creation conditions for MySQL Install MySQL** - Sets up and configures MySQL Create MySQL DB** - Establishes a new MySQL database with user access Delete MySQL DB** - Removes a MySQL database and user Format Output** - Structures the final workflow output Getting Started Guide Import the workflow into n8n Adjust parameters in the Set Parameters node Execute the workflow Confirm the database operation on the server Necessary Requirements SSH-enabled Linux server Root-level access rights Customization Options Switch db_type between PostgreSQL and MySQL Select action (install, create, delete) via the action parameter Tailor database_name, db_user, and db_password as needed Features Install Database Server - Deploys PostgreSQL or MySQL with optimal configuration Create Database - Generates new databases with assigned users and permissions Delete Database - Eliminates databases and their associated users Parameters to Configure server_host: Your Linux server IP address server_user: SSH username (typically 'root') server_password: SSH password db_type: Select 'postgresql' or 'mysql' action: Select 'install', 'create', or 'delete' database_name: Name of the database to create or delete db_user: Database username db_password: Database password How to Use Copy the JSON code from the artifact Access your n8n workspace Choose "Import from JSON" or "+" → "From JSON" Insert the JSON code Set parameters in the "Set Parameters" node with your server information Run the workflow Workflow Actions Install: Sets up the database server, enables remote access, and initializes the database Create: Establishes a new database with a specific user Delete: Erases the database and its associated user The workflow automatically manages Ubuntu/Debian package setup Service initialization and configuration Remote access setup User and permission assignments Authentication configuration Update the parameters in the "Set Parameters" node with your server specifics and execute the workflow!

Audio Generator – Documentation 🎯 Purpose: Generate audio files from text scripts stored in Google Drive. 🔁 Flow: Receive repo IDs. Fetch text scripts. Generate .wav files using local Bark model. Upload back to Drive. 📦 Dependencies: Python script: /scripts/generate_voice.py Bark (voice generation system) n8n instance with access to local shell Google Drive OAuth2 credentials ✏️ Notes: Script filenames must end with .txt Only works with plain text No external API used = 100% free 📦 /scripts/generate_voice.py: import sys import torch import numpy import re from bark import SAMPLE_RATE, generate_audio, preload_models from scipy.io.wavfile import write as write_wav Patch to allow numpy._core.multiarray.scalar during loading torch.serialization.add_safe_globals([numpy._core.multiarray.scalar]) Monkey patch torch.load to force weights_only=False _original_torch_load = torch.load def patched_torch_load(f, args, *kwargs): if 'weights_only' not in kwargs: kwargs['weights_only'] = False return _original_torch_load(f, args, *kwargs) torch.load = patched_torch_load Preload Bark models preload_models() def split_text(text, max_len=300): Split on punctuation to avoid mid-sentence cuts sentences = re.split(r'(?<=[.?!])\s+', text) chunks = [] current = "" for sentence in sentences: if len(current) + len(sentence) < max_len: current += sentence + " " else: chunks.append(current.strip()) current = sentence + " " if current: chunks.append(current.strip()) return chunks Input text file and output path input_text_path = sys.argv[1] output_wav_path = sys.argv[2] with open(input_text_path, 'r', encoding='utf-8') as f: full_text = f.read() voice_preset = "v2/en_speaker_7" chunks = split_text(full_text) Generate and concatenate audio chunks audio_arrays = [] for chunk in chunks: print(f"Generating audio for chunk: {chunk[:50]}...") audio = generate_audio(chunk, history_prompt=voice_preset) audio_arrays.append(audio) Merge all audio chunks final_audio = numpy.concatenate(audio_arrays) Write final .wav file write_wav(output_wav_path, SAMPLE_RATE, final_audio) print(f"Full audio generated at: {output_wav_path}") `

> Like this template? Connect with Eduard via LinkedIn. This workflow is a prototype of an AI-powered image editing interface, similar to Photoshop's Generative Fill feature, but running entirely in the browser. It provides a web-based editor that allows users to: Select areas in images using an adjustable brush tool Input text prompts to guide the AI generation Compare original and generated images side by side Iterate on edits with different prompts and settings Save or reuse generated images > 🎨 Perfect for product catalog management, seasonal content updates, and creative image editing tasks! 📋 Requirements FLUX API Access: You'll need API credentials from FLUX to use this workflow. Configure the HTTP Header Auth credential in n8n with your FLUX API key 🔧 Key Components FLUX Fill API for AI-powered image generation Konva.js for canvas manipulation img-comparison-slider for result visualization Custom CSS/JS for editor functionality Simple Editor Interface HTML page with an editor is served on the Webhook call Adjustable brush selection tool Provides several mock examples and allows uploading custom images Basic prompt and FLUX model parameter controls Image Processing Pipeline Handles image and mask separately Processes FLUX Fill API requests Delivers results back to the editor Result Viewer Split-screen comparison of original and generated images Interactive slider for before/after comparison Options to save or continue editing Support for multiple iteration cycles 🎯 Use Cases This prototype is particularly useful for: Testing AI-powered image editing concepts Quick product visualization experiments Exploring creative image variations Demonstrating inpainting capabilities > 💡 Pro Tip: Save masks for frequently edited areas to quickly generate variations with different prompts! The workflow can be extended to integrate with various data sources and can be customized for specific business needs.

This workflow provides automated access to the Notdaniel Voxtral Small 24B 2507 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 audio generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete audio generation process using the Notdaniel Voxtral Small 24B 2507 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: Voxtral Small is an enhancement of Mistral Small 3 that incorporates state-of-the-art audio input capabilities and excels at speech transcription, translation and audio understanding. Key Capabilities AI-driven audio generation and processing** High-quality sound synthesis** Advanced audio manipulation tools** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Notdaniel/voxtral-small-24b-2507 AI model Notdaniel Voxtral Small 24B 2507**: The core AI model for audio 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 Audio Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Music Production**: Generate background music and audio tracks Podcast Enhancement**: Create intro/outro music and sound effects Audio Content**: Produce voiceovers and audio narration Sound Design**: Generate custom audio for games and applications 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 #audiogeneration #aiaudio #soundgeneration #musicai #audioautomation #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

This workflow provides automated access to the Black Forest Labs Flux Schnell 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 Schnell 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: Advanced AI model by black-forest-labs for automated processing tasks. Key Capabilities High-quality image generation from text prompts** Advanced AI-powered visual content creation** Customizable image parameters and styles** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Black Forest Labs/flux-schnell AI model Black Forest Labs Flux Schnell**: 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

Are you looking to create a counseling chatbot that provides emotional support and mental health guidance through the LINE messaging platform ? This guide will walk you through connecting LINE with powerful AI language models like GPT-4 to build a chatbot that supports users in navigating their emotions, offering 24/7 conversational therapy and accessible mental health resources . By leveraging LINE's webhook integration and Azure OpenAI , this template allows you to design a chatbot that is both empathetic and efficient, ensuring users receive timely and professional responses. Whether you're a developer, counselor, or business owner, this guide will help you create a customizable counseling chatbot tailored to your audience's needs. Who Is This Template For? Developers who want to integrate AI-powered chatbots into the LINE platform for mental health applications. Counselors & Therapists looking to expand their reach and provide automated emotional support to clients outside of traditional sessions. Businesses & Organizations focused on improving mental health accessibility and offering innovative solutions to their users. Educators & Nonprofits seeking tools to provide free or low-cost counseling services to underserved communities. How this work? Line Webhook to receive new message Send loading animation in Line Check if the input is text or not Send the text as prompt in chat model (GPT 4o) Reply the message to user (you'll need 'edit field' to format it before reply) Pre-Requisites You have access to the LINE Developers Console. An Azure OpenAI account with necessary credentials. Set-up To receive messages from LINE, configure your webhook: Set up a webhook in LINE Developer Console. Copy the Webhook URL from the Line Chatbot node and paste it into the LINE Console. Ensure to remove any 'test' part when moving to production. The loading animation reassures users that the system is processing their request. Authorize using header authorization Message Handling Use the Check Message Type IsText? node to verify if the incoming message is text. If the message type is text, proceed with ChatGPT processing; otherwise, send a reply indicating non-text inputs are not supported. AI Agent Configuration Define the system message within the AI Agent node to guide the conversation based on desired interaction principles. Connect the Azure OpenAI Chat Model to the AI Agent. Formatting Responses Ensure responses are properly formatted before sending them back to the user. Reply Message Use the ReplyMessage - Line node to send the formatted response. Ensure proper header authorization using Bearer tokens.

Automatically Add Captions to Your Video Who Is This For? This workflow is ideal for content creators, marketers, educators, and businesses that regularly produce video content and want to enhance accessibility and viewer engagement by effortlessly adding subtitles. What Problem Does This Workflow Solve? Manually adding subtitles or captions to videos can be tedious and time-consuming. Accurate captions significantly boost viewer retention, accessibility, and SEO rankings. What Does This Workflow Do? This automated workflow quickly adds accurate subtitles to your video content by leveraging the Json2Video API. It accepts a publicly accessible video URL as input. It makes an HTTP request to Json2Video, where AI analyzes the video, generates captions, and applies them seamlessly. The workflow returns a URL to the final subtitled video. The second part of the workflow periodically checks the Json2Video API to monitor the processing status at intervals of 10 seconds. 👉🏻 Try Json2Video for Free 👈🏻 Key Features Automatic & Synced Captions:** Captions are generated automatically and synchronized perfectly with your video. Fully Customizable Design:** Easily adjust fonts, colors, sizes, and more to match your unique style. Word-by-Word Display:** Supports precise, word-by-word captioning for improved clarity and viewer engagement. Super Fast Processing:** Rapid caption generation saves time, allowing you to focus more on creating great content. Preconditions To use this workflow, you must have: A Json2Video API account. A video hosted at a publicly accessible URL. Why You Need This Workflow Adding subtitles to your videos significantly enhances their reach and effectiveness by: Improving SEO visibility, enabling search engines to effectively index your video content. Enhancing viewer engagement and accessibility, accommodating viewers who watch without sound or who have hearing impairments. Streamlining your content production process, allowing more focus on creativity. Specific Use Cases Social Media Content:** Boost viewer retention by adding subtitles. Educational Videos:** Enhance understanding and improve learning outcomes. Marketing Videos:** Reach broader and more diverse audiences.

This workflow gets the top 5 products from Product Hunt and shares them on the Discord server. Cron node: This node triggers the workflow every hour. Based on your use case, you can update the node to trigger the workflow at a different time. GraphQL node: This node makes the API call to the Product Hunt GraphQL API. You will need an API token from Product Hunt to make the call. Item Lists node: This node transforms the single item returned by the previous node into multiple items. Set node: The Set node is used to return only the name, description, and votes of the product. Discord node: This node is used to send the top 5 products to the Discord server.

This workflow demonstrates the use of the $item(index) method. This method is useful when you want to reference an item at a particular index. This example workflow makes POST HTTP requests to a dummy URL. Set node: This node is used to set the API key that will be used in the workflow later. This node returns a single item. This node can be replaced with other nodes, based on the use case. Customer Datastore node: This node returns the data of customers that will be sent in the body of the HTTP request. This node returns 5 items. This node can be replaced with other nodes, based on the use case. HTTP Request node: This node uses the information from both the Set node and the Customer Datastore node. Since, the node will run 5 times, once for each item of the Customer Datastore node, you need to reference the API Key 5 times. However, the Set node returns the API Key only once. Using the expression {{ $item(0).$node["Set"].json["apiKey"] }} you tell n8n to use the same API Key for all the 5 requests.

Description This n8n automation template delivers a full-stack AI content pipeline designed for marketing teams, content creators, SaaS founders, and growth hackers. It combines prompt chaining, GPT-4o agents, and Google Sheets to generate engaging, SEO-friendly blogs—end to end. What This Template Does: 📝 Generates blog topic ideas using a domain-specific AI agent (e.g., for Sparrow API testing) 📄 Creates a blog outline with key sections and headings ✅ Evaluates & refines the outline to ensure clarity, flow, and engagement 🧾 Writes the full blog content in structured, long-form paragraphs 📥 Appends the blog to Google Sheets with the current date Built With: GPT-4o (via Azure OpenAI) LangChain Agents for task-specialized prompt chaining Google Sheets integration for automatic publishing Schedule Trigger for periodic content generation Ideal Use Cases: SaaS teams looking to scale inbound content API platforms (like Sparrow) publishing technical how-tos SEO agencies automating client blog content Solo founders growing product visibility via thought leadership

This workflow automatically deletes user data from different apps/services when a specific slash command is issued in Slack. Watch this talk and demo to learn more about this use case. The demo uses Slack, but Mattermost is Slack-compatible, so you can also connect Mattermost in this workflow. Prerequisites Accounts and credentials for the apps/services you want to use. Some basic knowledge of JavaScript. Nodes Webhook node triggers the workflow when a Slack slash command is issued. IF nodes confirm Slack's verification token and verify that the data has the expected format. Set node simplifies the payload. Switch node chooses the correct path for the operation to perform. Respond to Webhook nodes send responses back to Slack. Execute Workflow nodes call sub-workflows tailored to deleting data from each individual service. Function node, Crypto node, and Airtable node generate and store a log entry containing a hash value. HTTP Request node sends the final response back to Slack.

Tags: Supply Chain Management, Logistics, Transportation, Data Transmission Context Hey! I'm Samir, a Supply Chain Engineer and Data Scientist from Paris founder of LogiGreen Consulting We help small and medium businesses improve their logistics processes using AI, Data Analytics and Automation. > Sustainable and Efficient supply chains with N8N! 📬 For business inquiries, you can add me on Here What is an EDI Message? Electronic Data Interchange (EDI) is a standardized method of automatically transferring data between computer systems. They ensure the smooth flow of essential transactional data, such as purchase orders, invoices, shipping notices, and more. For instance, a manufacturing company can receive purchase orders from a retailer via EDI. However, they need complex integration for the transmission and processing of the messages. Who is this template for? This workflow template is designed for small companies that cannot connect to their customers and need to manually process the EDI messages received. How does it work? This workflow uses a Gmail Trigger that analyzes all the incoming emails. 📧 Gmail Trigger → Detects emails with "EDI" in the subject. 📜 Parses EDI Message → Uses a JavaScript Code Node to extract structured data. 📊 Formats the Data → Converts it into a table-friendly format. 📑 Updates Google Sheets → Automatically logs the processed orders. Prerequisite This workflow does not require any additional paying subscription. A Google Drive Account with a folder including a Google Sheet API Credentials: Google Drive API, Google Sheets API and Gmail API A Google sheet to store the shipment records. You do not need to prepare the columns. Next Steps Follow the sticky notes to set up the parameters inside each node and get ready to improve your logistics operations! 📺 Watch the Step-by-Step Guide 🎥 Check My Tutorial 🚀 Interested in applications of N8N for Logistics & Supply Chain Management? Let's connect on Linkedin Notes This template includes an example of EDI message to test the workflow. If you want to learn more about Electronic Data Interchange: 🚚 Blog Article about Electronic Data Interchange (EDI) This workflow has been created with N8N 1.82.1 Submitted: March 19th, 2025