Workflow Templates

This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. Title: n8n Credentials and Workflows Backup on Change Detection Purpose: Never lose track of your n8n changes again! This workflow smartly backs up all your workflows and credentials, automatically detects any changes using hash comparison, and pushes updates to GitHub—but only when something has actually changed. Set your own interval and stop cluttering your repo with redundant commits. Walkthrough Video on YouTube Trigger: Schedule Trigger**: Executes the entire process at a user-defined interval. No need to worry about traceability or managing countless backups, as the workflow only commits changes when a difference is detected. Workflow Backup Process: Set Workflow Path: Defines the local backup file path for workflows. Get Old Workflow Hash: Executes a helper workflow to retrieve the previous hash. Execute Workflow Backup: Runs n8n export:workflow to export all workflows to the defined file path. Get New Workflow Hash: Executes a helper workflow to generate the new hash from the exported file. Compare Hashes (If Workflow Updated): Checks if the new hash differs from the old one. If Updated: Read Workflow Data → Extract Text → Push to GitHub: Reads, extracts, and commits the updated workflow JSON to GitHub under a timestamped filename. Credential Backup Process: Set Credential Path: Defines the local backup file path for credentials. Get Old Credential Hash: Executes a helper workflow to retrieve the previous hash. Execute Credential Backup: Runs n8n export:credentials to export all credentials. Get New Credential Hash: Executes a helper workflow to generate the new hash from the exported file. Compare Hashes (If Credential Updated): Checks for changes. If Updated: Read Credential Data → Extract Text → Push to GitHub: Commits the new credentials JSON to GitHub if changes are found. Hash Generator (Helper Flow): Used in both workflow and credential backup paths: Read File* → *Extract Text* → *Hash Data** Outputs SHA-256 hash used for comparison GitHub Integration: Commits are created with ISO timestamp in the filename and message. Repository: https://github.com/your-github-name/n8n-onchange-bachup File paths: backups/WorkFlow Backup -timestamp-.json and backups/Credential Backup -timestamp-.json Change Detection Logic: Only commits files when hash changes are detected (i.e., actual content change). Avoids unnecessary GitHub commits and storage use. Error Handling: GitHub nodes are set to continue workflow execution on error, avoiding full process interruption.

**Get Started ** Creator: @obisdev This workflow powers a fully automated WhatsApp chatbot using a self-hosted Venom Bot instead of the official WhatsApp Business API. It integrates Google Gemini AI to generate intelligent, conversational responses and optionally pulls factual information from a Google Docs-based knowledge base. Designed for small businesses and creators, the bot can maintain contextual memory across messages and act as a smart virtual assistant for sales, support, and lead generation. Overview This n8n workflow connects with a custom-hosted Venom Bot that simulates WhatsApp Web to send and receive messages. It uses a Webhook trigger to receive incoming messages, processes them with an AI Agent powered by Gemini, optionally pulls extra data from a Google Doc or Google Sheet, and sends a smart reply back through the Venom Bot. The workflow also includes a memory system to retain user context, making it capable of handling follow-up questions and dynamic conversations. Who this workflow is for Small Business Owners: Offer 24/7 customer service on WhatsApp without paying for Meta’s Business API. Freelancers & Developers: Build, test, and monetize intelligent bots without the approval process of WhatsApp’s API. Online Sellers & Creators: Handle FAQs, orders, and customer inquiries via WhatsApp on autopilot. Marketers: Deploy campaign bots that respond to DMs with personalized product suggestions or lead captures. Hackers & Builders: Experiment with unofficial APIs to control WhatsApp reliably without breaking TOS for small-scale use. Tools Used n8n: The automation platform managing flow, context, and decision logic. Venom Bot: A Node.js-based, self-hosted WhatsApp Web bot used to send/receive messages. Google Gemini: AI engine for generating context-aware replies. Google Docs (Optional): Acts as a structured knowledge base for business info or FAQs. Google Sheets (Optional): Feeds real-time or structured data into your AI responses. How to Install Import the Workflow: Download the .json and import it into your n8n instance. Set Up Venom Bot: Deploy Venom Bot (on VPS or local) and set it to send messages to your Webhook URL. Webhook Configuration: Update the Webhook node in n8n and set 'Respond' to "Using Respond to Webhook Node". Connect Google Gemini: Add your Gemini API key in n8n credentials. Set Up Google Docs (Optional): Link the document containing your knowledge base. Enable Conversational Memory: Use ={{ $("Process Message").first().json.from }} as the session ID. Check API Key Matching: Ensure the API_SECRET_KEY in Venom .env matches the authorization header in n8n. Customize Persona & Prompts: Update the AI Agent system message to fit your brand tone. Use Cases Customer service without WhatsApp Business API Smart lead generation bots E-commerce order responders AI-powered chatbot for DMs FAQ responder with knowledge base support Connect with Me Email: obisdev@gmail.com Twitter/X: @obisdev GitHub: github.com/obisdev Visit: obisdev.vercel.app #n8n #whatsappautomation #venombot #chatbots #noapi #geminiapi #googleworkspace #aiassistant #nocode #vpsautomation #chatbotwithoutapi #automationtools #customerbot #salesautomation #googleintegration

This n8n workflow collects and summarizes news from multiple RSS feeds, using OpenAI to generate a concise summary that can be sent to WhatsApp or other destinations. Perfect for automating your daily news digest. 🔁 Workflow Breakdown: Schedule Trigger Start the workflow on your desired schedule (daily, hourly, etc.). 🟨 Note: Set the trigger however you wish. RSS Feeds (My RSS 01–04) Fetches articles from four different RSS sources. 🟨 Note: You can add as many RSS feeds as you want. Edit Fields (Edit Fields1–3) Normalizes RSS fields (title, link, etc.) to ensure consistency across different sources. Merge (append mode) Combines the RSS items into a single unified list. Filter Optionally filter articles by keywords, date, or categories. Limit Limits the analysis to the 10 most recent articles. 🟨 Note: This keeps the result concise and avoids overloading the summary. Aggregate Prepares the selected news for summarization by combining them into a single content block. OpenAI (Message Assistant) Summarizes the aggregated news items in a clean and readable format using AI. Send Summary to WhatsApp Sends the AI-generated summary to a WhatsApp endpoint via webhook (yoururlapi.com). You can replace this with an email service, Google Drive, or any other destination. 🟨 Note: You can send it to your WhatsApp API, email, drive, etc. No Operation (End) Final placeholder to safely close the workflow. You may expand from here if needed.

This AI agent can access data provided by another n8n workflow. Since that workflow can be used to retrieve any data from any service, this template can be used give an agent access to any data. Note that to use this template, you need to be on n8n version 1.19.4 or later.

PersonalNotesAssistant – Organize and Understand Your Thoughts with Local AI PersonalNotesAssistant is an offline-capable, AI-powered agent that helps you store, summarize, retrieve, and reflect on your personal notes and voice memos — all processed locally and sent via Telegram. Built to run efficiently on a Raspberry Pi 5, this agent supports a variety of note-taking styles and acts as your private memory extension. 🧠 What It Can Do Accept voice or text notes via Telegram Transcribe audio messages into clean, structured text (using Whisper) Automatically summarize or categorize notes with a local LLM Answer questions based on your past notes Retrieve relevant entries by topic, date, or keyword Help you journal or reflect by asking follow-up questions Work completely offline — no cloud or external APIs 🔧 How It Works Capture Notes via Telegram You send a voice message or text to your Telegram bot. The assistant supports both quick thoughts and long-form content. Transcription with Whisper (Local) If the input is a voice message, it is transcribed into text using Whisper running locally on your Raspberry Pi. AI Summarization & Tagging The transcribed or typed note is sent to LLaMA 3.2 via Ollama, which summarizes it, suggests tags, and stores it with metadata (e.g., timestamp, mood, theme). Storage & Retrieval Notes are stored in a local database (e.g., SQLite or JSON). You can later query the assistant with prompts like: “What did I say about stress last week?” “Summarize my ideas from this month.” “Show notes tagged with 'travel'.” Follow-Up & Reflection The agent can optionally engage with reflective prompts to help you deepen your thoughts or gain insight from what you’ve recorded. 💡 Use Cases Track personal growth, habits, or therapy progress Create voice memos while walking or commuting Maintain a structured journal without typing Use as a second brain to help you remember and revisit important thoughts 🔐 Privacy by Default Everything runs locally: No notes are uploaded to cloud platforms No audio is sent to third-party transcription services No LLM processing happens outside your device Ideal for privacy-minded users, psychologists, researchers, or digital minimalists who want AI assistance without surveillance. ⚙️ Technical Stack Raspberry Pi 5: Low-power edge device Whisper (local): For voice-to-text conversion Ollama + LLaMA 3.2: For summarization, classification, and retrieval Telegram Bot API: For input/output Custom Database (e.g., JSON/SQLite): For storing and querying notes 🧪 Real-Life Use This agent is actively used daily by the developer to log ideas, emotions, and plans. It has proven effective for lightweight journaling and context-aware memory assistance, even when offline.

BACKGROUND Malaysia's Inland Revenue (LHDN) provides an API to get the tax id number for a business entity, based on a given Business Registration number (BRN or SSM), or NRIC (MyKad). PROBLEM However, the API only allows one search at a time. SOLUTION This free workflow lets you do a batch search to get TIN for multiple SSM or NRIC. This is useful if you need to prepare your internal DB for e-invoicing PRE-REQUISITES 1) Get your connection client id and client secret from myhasil.gov.my website 2) Prepare your Google Sheet containing a list of SSM and NRIC you want to get the TIN 3) Create N8N credential to connect to your google sheet above SUPPORT Questions? Ask alex at halfborg dot com

This n8n workflow sends SMS messages through the Textbelt API by accepting phone numbers, messages, and API keys as inputs. It uses a manual trigger to start the process, sets the necessary data, and executes an HTTP POST request to deliver the SMS. Step-by-Step Explanation: Manual Trigger: Starts the workflow manually by clicking ‘Execute workflow’. Set Data Node: Defines the required input parameters (phone, message, and key) that will be sent to the SMS API. You can populate these fields with your target phone number, the text message, and your Textbelt API key. HTTP Request Node: Sends a POST request to https://textbelt.com/tex with the phone number, message, and API key in the request body to send the SMS. The response from the API confirms whether the message was successfully sent.

This workflow helps you generate an llms.txt file (if you're unfamiliar with it, check out this article) using a Screaming Frog export. Screaming Frog is a well-known website crawler. You can easily crawl a website. Then, export the "internal_html" section in CSV format. How It Works: A form allows you to enter: The name of the website A short description The internal_html.csv file from your Screaming Frog export Once the form is submitted, the workflow is triggered automatically, and you can download the llms.txt file directly from n8n. Downloading the File Since the last node in this workflow is "Convert to File", you will need to download the file directly from the n8n UI. However, you can easily add a node (e.g., Google Drive, OneDrive) to automatically upload the file wherever you want. AI-Powered Filtering (Optional): This workflow includes a text classifier node, which is deactivated by default. You can activate it to apply a more intelligent filter to select URLs for the llms.txt file. Consider modifying the description in the classifier node to specify the type of URLs you want to include. How to Use This Workflow Crawl the website you want to generate an llms.txt file for using Screaming Frog. Export the "internal_html" section in CSV format. In n8n, click "Test Workflow", fill in the form, and upload the internal_html.csv file. Once the workflow is complete, go to the "Export to File" node and download the output. That's it! You now have your llms.txt file! Recommended Usage: Use this workflow directly in the n8n UI by clicking 'Test Workflow' and uploading the file in the form.

Use case This workflow is designed for e-commerce brands and content teams who: Need to scale SEO content production without sacrificing quality Want to eliminate manual keyword filtering (saves 10+ hours/week) Aim to dominate niche search terms (e.g., "vegan leather crossbody bags") What this workflow does Automates the end-to-end process from keyword discovery to publish-ready articles: Keyword Harvesting: Pulls 1,000+ keywords/day from SEMrush/Ahrefs Smart Filtering:Blocks competitor brands (e.g., "Zara alternatives") Detects irrelevant demographics ("kids", "petite") AI Content Generation:Flags non-compliant colors (non-black/white terms) Multi-Channel Output: Formats content for blogs, product descriptions, and email campaigns setup Add Google,SEMrush and OpenAI credentials Set the rules excel of google drive Test workflow by testing workflow Review generated opportunity report in Google Sheets How to adjust this template Change scenario: Replace the rules and define different target

An automated n8n workflow that analyzes stocks using RSI and MACD, summarizes insights with OpenAI, and sends a Slack-ready market update every hour. This workflow: Runs hourly from 6:30 AM to 2:30 PM PT, Mon–Fri Checks if the U.S. stock market is open using Alpaca’s /clock API Pulls daily stock bars for a list of tickers via Alpaca’s /v2/stocks/bars Calculates RSI and MACD using a Python code node Categorizes each stock as Buy / Hold / Sell Uses OpenAI Assistant to summarize the results in Slack markdown Sends the message to a specific Slack user or channel

This workflow automatically identifies trending topics and hashtags across social media platforms to keep you informed of current trends and viral content. It saves you time by eliminating the need to manually research trending topics and provides data-driven insights for content strategy and social media planning. Overview This workflow automatically scrapes trending hashtag platforms and social media sites to extract currently trending topics, hashtags, and viral content themes. It uses Bright Data to access trend data sources without restrictions and AI to intelligently analyze trending content and provide actionable insights for content creators and marketers. Tools Used n8n**: The automation platform that orchestrates the workflow Bright Data**: For scraping trend platforms and social media without being blocked OpenAI**: AI agent for intelligent trend analysis and content insights Google Sheets**: For storing trending topics 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 trending topics tracking spreadsheet Customize: Define target trend platforms and topics of interest Use Cases Content Marketing**: Discover trending topics for timely and relevant content creation Social Media Strategy**: Plan posts around viral hashtags and trending themes Brand Monitoring**: Track if your brand or industry topics are trending Influencer Marketing**: Identify trending content opportunities for collaborations 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 #trendingtopics #hashtags #brightdata #webscraping #contentmarketing #n8nworkflow #workflow #nocode #socialmediatrends #trendanalysis #viralcontent #contentresearch #socialmediamonitoring #trendtracking #contentdiscovery #hashtagresearch #socialmediamarketing #contentautomation #trendmonitoring #socialmediainsights #contentplanning #trendalerts #viralmarketing #socialtrends #contentoptimization #trendingcontent #socialmediadata #contentintelligence

Ever wanted to just tell your 3d printer what to do remotely? This game changer let's you converse with OpenAI agents to manage OctoPrint connected 3d printers. Great for remote management and monitoring with easy to read responses. Query what jobs are available, Load a print job (upload workflow in development, will be released soon for community use), start the print job and request detailed reports on your printers performance as it runs. Chat > AI > OctoPrint API > Your 3d Printer ++Example 1:++ Human Input: "What print job is running?" AI Response: Current Print Job Details, Job Name: Stand v1.gcode File Size: 2,533,233 bytes Estimated Print Time: Approximately 6 hours 15 minutes (22536 seconds) Progress: Completion: 1.97%, Current Position in File: 49,940 bytes, Time Spent Printing: 2,611 seconds (~43.5 minutes), Time Remaining: Approximately 5 hours 34 minutes (20,123 seconds), Status, Current State: Printing." ++Example 2++ Human Input: "Is my 3d Printer ok?" AI Response: "Status: Printing, Operational: Yes, ++Temperature:++ Bed Temperature: Actual: 50°C, Target: 50°C, Nozzle (Tool 0) Temperature: Actual: 200°C, Target: 200°C, ++Connection Status:++ Connection State: Currently connected to the printer, Port: /dev/ttyUSB0, Baudrate: 115200, Summary, Your 3D printer is currently operational and printing without errors. The bed and nozzle temperatures are both at their target values."